技术领域Technical Field
本发明涉及医疗数据处理技术领域，尤其涉及一种基于人体成分的透析干体重分析方法及系统。The present invention relates to the technical field of medical data processing, and in particular to a dialysis dry weight analysis method and system based on human body composition.
背景技术Background Art
透析（dialysis）是一种通过小分子经过半透膜扩散到水（或缓冲液）的原理，将小分子与生物大分子分开的分离纯化技术。在医学上，透析主要用于治疗因肾功能损害而发生的急、慢性肾功能衰竭，也偶尔用于清除病人体内已被吸收的药物或其他毒物。透析患者常存在水钠潴留的问题，水分过多或过少都会对身体健康产生不良影响。干体重，也称“目标体重”，即水在正常平衡条件下的体重，表明患者既没有水潴留，也没有脱水时的体重，也就是血液透析结束时希望达到的体重。通过控制干体重，可以维持水盐平衡，减少水肿或低血容量等并发症的发生。这是透析治疗过程中的一个重要目标，有助于保持患者体内环境的稳定。血液透析过程中，过高的干体重可能导致高血压、心力衰竭等心血管疾病的发生。这是因为水钠潴留会增加心脏的负担，导致心脏功能受损。通过保持合适的干体重，可以显著降低这些心血管并发症的风险，保护患者的心脏健康。进行透析干体重分析对于评估透析液超滤量、指导透析治疗、促进患者自我管理和提高治疗安全性等方面都具有重要意义。Dialysis is a separation and purification technology that separates small molecules from biomacromolecules by the principle of diffusion of small molecules into water (or buffer) through a semipermeable membrane. In medicine, dialysis is mainly used to treat acute and chronic renal failure caused by renal damage, and is occasionally used to remove drugs or other toxins that have been absorbed by the patient's body. Patients on dialysis often have problems with water and sodium retention. Too much or too little water can have adverse effects on physical health. Dry weight, also known as "target weight", is the weight of water under normal balance conditions, indicating that the patient has neither water retention nor dehydration, which is the weight that is hoped to be achieved at the end of hemodialysis. By controlling dry weight, water and salt balance can be maintained and complications such as edema or hypovolemia can be reduced. This is an important goal during dialysis treatment and helps to maintain a stable internal environment in the patient. During hemodialysis, excessive dry weight may lead to the occurrence of cardiovascular diseases such as hypertension and heart failure. This is because water and sodium retention increases the burden on the heart and leads to impaired heart function. By maintaining an appropriate dry weight, the risk of these cardiovascular complications can be significantly reduced and the heart health of patients can be protected. Dialysis dry weight analysis is of great significance in evaluating the ultrafiltration volume of dialysate, guiding dialysis treatment, promoting patient self-management and improving treatment safety.
现有技术中，为了对患者的理想干体重进行预测，主要依靠透析患者的临床表现和患者的主观感受，具体地，根据透析患者的临床表现和患者的主观感受测定，如有无浮肿、胸闷、高血压、体腔积液及肺淤血等。然而，该方法受患者主观因素、疾病、饮食、营养状况等影响。更严重的是，只有当水负荷显著增高后患者才表现为以上症状体征，因而该方法判断体液是否超负荷极不敏感。In the prior art, in order to predict the ideal dry weight of patients, the method mainly relies on the clinical manifestations of dialysis patients and the subjective feelings of patients. Specifically, the method is determined based on the clinical manifestations of dialysis patients and the subjective feelings of patients, such as the presence or absence of edema, chest tightness, hypertension, body cavity effusion and pulmonary congestion. However, this method is affected by the patient's subjective factors, diseases, diet, nutritional status, etc. More seriously, the patient will only show the above symptoms and signs when the water load increases significantly, so this method is extremely insensitive to judging whether the body fluid is overloaded.
因此，还需要提供一种基于人体成分的透析干体重分析方法及系统，用于提高透析干体重分析的准确性及实时性。Therefore, there is a need to provide a dialysis dry weight analysis method and system based on human body composition to improve the accuracy and real-time performance of dialysis dry weight analysis.
发明内容Summary of the invention
本发明提供了一种基于人体成分的透析干体重分析系统，包括：样本获取模块，用于获取多个样本透析患者的干体重相关信息，其中，所述干体重相关信息包括基础信息、人体成分信息、生理参数信息、标记物水平信息、阻抗频率矩阵以及干体重信息；数据分析模块，用于基于所述多个样本透析患者的基础信息，对所述多个样本透析患者进行聚类，确定多个样本簇，对于每个所述样本簇，基于所述样本簇包括的每个样本透析患者的干体重相关信息，确定所述样本簇对应的最优阻抗采集位置及最优阻抗采集参数；成分采集模块，用于获取待分析透析患者的基础信息，基于所述待分析透析患者的基础信息，确定目标样本簇，基于所述目标样本簇对应的最优阻抗采集位置及最优阻抗采集参数，采集所述待分析透析患者的阻抗信息，还用于采集所述待分析透析患者的人体成分信息、生理参数信息及标记物水平信息；干体重分析模块，用于基于所述待分析透析患者的阻抗信息、人体成分信息、生理参数信息及标记物水平信息，对所述待分析透析患者的干体重进行分析。The present invention provides a dialysis dry weight analysis system based on human body composition, comprising: a sample acquisition module, used to acquire dry weight related information of multiple sample dialysis patients, wherein the dry weight related information includes basic information, human body composition information, physiological parameter information, marker level information, impedance frequency matrix and dry weight information; a data analysis module, used to cluster the multiple sample dialysis patients based on the basic information of the multiple sample dialysis patients, determine multiple sample clusters, and for each of the sample clusters, determine the optimal impedance acquisition position and optimal impedance acquisition parameters corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster; a component acquisition module, used to acquire the basic information of the dialysis patient to be analyzed, determine the target sample cluster based on the basic information of the dialysis patient to be analyzed, collect the impedance information of the dialysis patient to be analyzed based on the optimal impedance acquisition position and optimal impedance acquisition parameters corresponding to the target sample cluster, and also used to collect the human body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed; a dry weight analysis module, used to analyze the dry weight of the dialysis patient to be analyzed based on the impedance information, human body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed.
更进一步地，所述样本获取模块获取样本透析患者的阻抗频率矩阵，包括：获取所述样本透析患者在多种测试频率下的整体阻抗信息；获取所述样本透析患者在所述多种测试频率下的多个测试节段的节段阻抗信息；基于所述样本透析患者在多种测试频率下的整体阻抗信息和多个测试节段的节段阻抗信息，生成所述样本透析患者的阻抗频率矩阵。Furthermore, the sample acquisition module acquires the impedance frequency matrix of the sample dialysis patient, including: acquiring the overall impedance information of the sample dialysis patient at multiple test frequencies; acquiring the segment impedance information of multiple test segments of the sample dialysis patient at the multiple test frequencies; and generating the impedance frequency matrix of the sample dialysis patient based on the overall impedance information of the sample dialysis patient at multiple test frequencies and the segment impedance information of multiple test segments.
更进一步地，所述数据分析模块基于所述多个样本透析患者的基础信息，对所述多个样本透析患者进行聚类，确定多个样本簇，包括：基于任意两个所述样本透析患者的基础信息，计算任意两个所述样本透析患者的基础信息相似度；基于任意两个所述样本透析患者的基础信息相似度，对所述多个样本透析患者进行聚类，确定所述多个样本簇。Furthermore, the data analysis module clusters the multiple sample dialysis patients based on the basic information of the multiple sample dialysis patients to determine multiple sample clusters, including: calculating the basic information similarity of any two of the sample dialysis patients based on the basic information of any two of the sample dialysis patients; clustering the multiple sample dialysis patients based on the basic information similarity of any two of the sample dialysis patients to determine the multiple sample clusters.
更进一步地，所述数据分析模块基于所述样本簇包括的每个样本透析患者的干体重相关信息，确定所述样本簇对应的最优阻抗采集位置，包括：基于所述样本簇包括的每个样本透析患者在多种测试频率下的整体阻抗信息和多个测试节段的节段阻抗信息，计算每个所述测试节段对应的节段阻抗相关参数；基于所述样本簇包括的每个样本透析患者在多种测试频率下的多个测试节段的节段阻抗信息，计算每个所述测试节段对应的节段阻抗相似参数；基于每个所述测试节段对应的节段阻抗相关参数和节段阻抗相似参数，确定目标节段；基于所述目标节段，确定所述样本簇对应的最优阻抗采集位置。Furthermore, the data analysis module determines the optimal impedance acquisition position corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster, including: calculating the segment impedance related parameters corresponding to each test segment based on the overall impedance information of each sample dialysis patient included in the sample cluster at multiple test frequencies and the segment impedance information of multiple test segments; calculating the segment impedance similarity parameters corresponding to each test segment based on the segment impedance information of multiple test segments of each sample dialysis patient included in the sample cluster at multiple test frequencies; determining the target segment based on the segment impedance related parameters and segment impedance similarity parameters corresponding to each test segment; and determining the optimal impedance acquisition position corresponding to the sample cluster based on the target segment.
更进一步地，所述数据分析模块基于所述样本簇包括的每个样本透析患者的干体重相关信息，确定所述样本簇对应的最优阻抗采集参数，包括：确定所述样本簇的候选整体阻抗采集频率方案；确定所述样本簇的每个目标节段对应的候选节段阻抗采集频率方案；基于所述样本簇的候选整体阻抗采集频率方案和每个目标节段对应的候选节段阻抗采集频率方案，确定所述样本簇对应的最优阻抗采集参数。Furthermore, the data analysis module determines the optimal impedance acquisition parameters corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster, including: determining the candidate overall impedance acquisition frequency scheme of the sample cluster; determining the candidate segment impedance acquisition frequency scheme corresponding to each target segment of the sample cluster; and determining the optimal impedance acquisition parameters corresponding to the sample cluster based on the candidate overall impedance acquisition frequency scheme of the sample cluster and the candidate segment impedance acquisition frequency scheme corresponding to each target segment.
更进一步地，所述数据分析模块确定所述样本簇的候选整体阻抗采集频率方案，包括：对于所述样本簇包括的每个样本透析患者，基于所述样本透析患者在多种测试频率下的整体阻抗信息，拟合所述样本透析患者对应的整体阻抗频率测试曲线；重复执行对所述多种测试频率进行抽样，对于所述样本簇包括的每个样本透析患者，基于所述样本透析患者在抽样的测试频率下的整体阻抗信息，拟合整体阻抗频率预测曲线，基于所述整体阻抗频率预测曲线与所述整体阻抗频率测试曲线之间的相似度，计算整体抽样有效参数，直至满足预设抽样条件，基于每种抽样方案对应的整体抽样有效参数，确定候选整体阻抗采集频率方案。Furthermore, the data analysis module determines the candidate overall impedance acquisition frequency schemes of the sample cluster, including: for each sample dialysis patient included in the sample cluster, based on the overall impedance information of the sample dialysis patient at multiple test frequencies, fitting the overall impedance frequency test curve corresponding to the sample dialysis patient; repeatedly sampling the multiple test frequencies, for each sample dialysis patient included in the sample cluster, based on the overall impedance information of the sample dialysis patient at the sampled test frequency, fitting an overall impedance frequency prediction curve, based on the similarity between the overall impedance frequency prediction curve and the overall impedance frequency test curve, calculating the overall sampling effective parameters, until the preset sampling conditions are met, and determining the candidate overall impedance acquisition frequency scheme based on the overall sampling effective parameters corresponding to each sampling scheme.
更进一步地，所述数据分析模块确定所述样本簇的每个目标节段对应的候选节段阻抗采集频率方案，包括：对于所述样本簇包括的每个样本透析患者，基于所述样本透析患者在所述多种测试频率下的多个测试节段的节段阻抗信息，拟合所述样本透析患者的每个目标节段对应的节段阻抗频率测试曲线；对于每种所述目标节段，重复执行对所述多种测试频率进行抽样，对于所述样本簇包括的每个样本透析患者，基于所述样本透析患者在抽样的测试频率下的目标节段的节段阻抗信息，拟合节段阻抗频率预测曲线，基于所述节段阻抗频率预测曲线与所述节段阻抗频率测试曲线之间的相似度，计算节段抽样有效参数，直至满足预设抽样条件，基于每种抽样方案对应的节段抽样有效参数，确定目标节段对应的候选节段阻抗采集频率方案。Furthermore, the data analysis module determines a candidate segment impedance acquisition frequency scheme corresponding to each target segment of the sample cluster, including: for each sample dialysis patient included in the sample cluster, based on the segment impedance information of multiple test segments of the sample dialysis patient at the multiple test frequencies, fitting a segment impedance frequency test curve corresponding to each target segment of the sample dialysis patient; for each of the target segments, repeatedly sampling the multiple test frequencies, for each sample dialysis patient included in the sample cluster, based on the segment impedance information of the target segment of the sample dialysis patient at the sampled test frequency, fitting a segment impedance frequency prediction curve, based on the similarity between the segment impedance frequency prediction curve and the segment impedance frequency test curve, calculating segment sampling effective parameters until the preset sampling conditions are met, and determining the candidate segment impedance acquisition frequency scheme corresponding to the target segment based on the segment sampling effective parameters corresponding to each sampling scheme.
更进一步地，所述数据分析模块还用于：基于所述样本簇包括的每个样本透析患者的干体重相关信息，建立所述样本簇对应的阻抗修正模型和干体重分析模型；所述干体重分析模块基于所述待分析透析患者的阻抗信息、人体成分信息、生理参数信息及标记物水平信息，对所述待分析透析患者的干体重进行分析，包括：通过所述目标样本簇对应的阻抗修正模型，基于所述待分析透析患者的人体成分信息及生理参数信息，对所述待分析透析患者的阻抗信息进行修正；通过所述目标样本簇对应的干体重分析模型，基于修正后的阻抗信息和所述标记物水平信息，对待分析透析患者的干体重进行分析。Furthermore, the data analysis module is also used to: establish an impedance correction model and a dry weight analysis model corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster; the dry weight analysis module analyzes the dry weight of the dialysis patient to be analyzed based on the impedance information, body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed, including: correcting the impedance information of the dialysis patient to be analyzed based on the body composition information and physiological parameter information of the dialysis patient to be analyzed through the impedance correction model corresponding to the target sample cluster; analyzing the dry weight of the dialysis patient to be analyzed based on the corrected impedance information and the marker level information through the dry weight analysis model corresponding to the target sample cluster.
更进一步地，所述数据分析模块基于所述样本簇包括的每个样本透析患者的干体重相关信息，建立所述样本簇对应的阻抗修正模型，包括：基于所述样本簇包括的每个样本透析患者的干体重相关信息，确定每种生理参数与所述样本簇的相关参数，基于每种生理参数与所述样本簇的相关参数，确定目标生理参数；基于所述样本簇包括的每个样本透析患者的干体重相关信息和所述目标生理参数，建立所述样本簇对应的阻抗修正模型。Furthermore, the data analysis module establishes an impedance correction model corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster, including: determining the relevant parameters of each physiological parameter and the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster, and determining the target physiological parameters based on the relevant parameters of each physiological parameter and the sample cluster; establishing the impedance correction model corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster and the target physiological parameters.
本发明提供了一种基于人体成分的透析干体重分析方法，包括：获取多个样本透析患者的干体重相关信息，其中，所述干体重相关信息包括基础信息、人体成分信息、生理参数信息、标记物水平信息、阻抗频率矩阵以及干体重信息；基于所述多个样本透析患者的基础信息，对所述多个样本透析患者进行聚类，确定多个样本簇；对于每个所述样本簇，基于所述样本簇包括的每个样本透析患者的干体重相关信息，确定所述样本簇对应的最优阻抗采集位置及最优阻抗采集参数；获取待分析透析患者的基础信息，基于所述待分析透析患者的基础信息，确定目标样本簇；基于所述目标样本簇对应的最优阻抗采集位置及最优阻抗采集参数，采集所述待分析透析患者的阻抗信息；采集所述待分析透析患者的人体成分信息、生理参数信息及标记物水平信息；基于所述待分析透析患者的阻抗信息、人体成分信息、生理参数信息及标记物水平信息，对所述待分析透析患者的干体重进行分析。The present invention provides a dialysis dry weight analysis method based on human body composition, comprising: obtaining dry weight related information of multiple sample dialysis patients, wherein the dry weight related information includes basic information, human body composition information, physiological parameter information, marker level information, impedance frequency matrix and dry weight information; clustering the multiple sample dialysis patients based on the basic information of the multiple sample dialysis patients to determine multiple sample clusters; for each of the sample clusters, determining the optimal impedance acquisition position and optimal impedance acquisition parameters corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster; obtaining the basic information of the dialysis patient to be analyzed, and determining the target sample cluster based on the basic information of the dialysis patient to be analyzed; based on the optimal impedance acquisition position and optimal impedance acquisition parameters corresponding to the target sample cluster, acquiring the impedance information of the dialysis patient to be analyzed; acquiring the human body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed; and analyzing the dry weight of the dialysis patient to be analyzed based on the impedance information, human body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed.
相比于现有技术，本说明书提供的一种基于人体成分的透析干体重分析方法及系统，至少具备以下有益效果：Compared with the prior art, the dialysis dry weight analysis method and system based on human body composition provided in this specification has at least the following beneficial effects:
通过聚类分析，将透析患者分为不同的样本簇，每个簇内的患者具有相似的特征。这种个性化的分类使得后续分析更加精准，能够针对每个簇的特性制定最优的阻抗采集位置和参数，从而提高干体重评估的准确性和个性化程度。Through cluster analysis, dialysis patients are divided into different sample clusters, and patients in each cluster have similar characteristics. This personalized classification makes subsequent analysis more accurate and can formulate the optimal impedance collection location and parameters based on the characteristics of each cluster, thereby improving the accuracy and personalization of dry weight assessment.
确定每个样本簇的最优阻抗采集位置和参数后，可以显著减少在数据采集过程中的试错和调整时间。对于新加入的待分析患者，只需根据其基础信息快速确定所属样本簇，然后直接应用该簇的最优采集设置，大大提高了评估效率。After determining the optimal impedance acquisition position and parameters for each sample cluster, the trial and error and adjustment time during data acquisition can be significantly reduced. For newly added patients to be analyzed, it is only necessary to quickly determine the sample cluster to which they belong based on their basic information, and then directly apply the optimal acquisition settings for the cluster, greatly improving the evaluation efficiency.
并且，本系统和方法不仅考虑了阻抗信息，还结合了人体成分信息、生理参数信息及标记物水平信息等多种数据源。这种多源信息融合的方式能够更全面、准确地反映患者的生理状态，从而提高干体重评估的可靠性和准确性。Furthermore, the system and method not only consider impedance information, but also combine multiple data sources such as human body composition information, physiological parameter information, and marker level information. This multi-source information fusion method can more comprehensively and accurately reflect the patient's physiological state, thereby improving the reliability and accuracy of dry weight assessment.
进一步的，准确的干体重评估是制定和调整透析治疗方案的重要依据。通过本系统和方法，医生可以及时了解患者的干体重状况，并据此调整透析频率、透析时间、透析液浓度等参数，以达到更好的治疗效果，减少并发症的发生。Furthermore, accurate dry weight assessment is an important basis for formulating and adjusting dialysis treatment plans. Through the system and method, doctors can timely understand the patient's dry weight status and adjust parameters such as dialysis frequency, dialysis time, and dialysate concentration accordingly to achieve better treatment effects and reduce the occurrence of complications.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
本说明书将以示例性实施例的方式进一步说明，这些示例性实施例将通过附图进行详细描述。这些实施例并非限制性的，在这些实施例中，相同的编号表示相同的结构，其中：This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:
图1是本申请一实施例中示出的一种基于人体成分的透析干体重分析系统的模块图；FIG1 is a module diagram of a dialysis dry weight analysis system based on human body composition shown in an embodiment of the present application;
图2是本申请一实施例中示出的一种基于人体成分的透析干体重分析方法的流程图。FIG. 2 is a flow chart of a dialysis dry weight analysis method based on human body composition shown in an embodiment of the present application.
具体实施方式DETAILED DESCRIPTION
为了更清楚地说明本说明书实施例的技术方案，下面将对实施例描述中所需要使用的附图作简单的介绍。In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following briefly introduces the drawings required for describing the embodiments.
图1是本申请一实施例中示出的一种基于人体成分的透析干体重分析系统的模块图，如图1所示，一种基于人体成分的透析干体重分析系统包括样本获取模块、数据分析模块、成分采集模块及干体重分析模块。FIG1 is a module diagram of a dialysis dry body weight analysis system based on human body composition shown in an embodiment of the present application. As shown in FIG1 , a dialysis dry body weight analysis system based on human body composition includes a sample acquisition module, a data analysis module, a component acquisition module and a dry body weight analysis module.
样本获取模块可以用于获取多个样本透析患者的干体重相关信息。The sample acquisition module can be used to obtain dry weight related information of multiple sample dialysis patients.
其中，干体重相关信息包括基础信息、人体成分信息、生理参数信息、标记物水平信息、阻抗频率矩阵以及干体重信息。基础信息可以包括姓名、年龄、性别、身高、体重及病史。人体成分信息可以包括电解质浓度、红细胞计数及蛋白浓度。生理参数信息可以包括体温、血压信息等。标记物水平信息可以包括心房利钠肽水平及B型尿钠肽水平等。Among them, the dry weight related information includes basic information, human body composition information, physiological parameter information, marker level information, impedance frequency matrix and dry weight information. Basic information may include name, age, gender, height, weight and medical history. Human body composition information may include electrolyte concentration, red blood cell count and protein concentration. Physiological parameter information may include body temperature, blood pressure information, etc. Marker level information may include atrial natriuretic peptide level and B-type natriuretic peptide level, etc.
在一些实施例中，样本获取模块获取样本透析患者的阻抗频率矩阵，包括：In some embodiments, the sample acquisition module acquires an impedance frequency matrix of a sample dialysis patient, including:
获取样本透析患者在多种测试频率下的整体阻抗信息，具体的，测试频率可以在预设频率范围内，例如，在10 Hz到100 kHz范围内，在样本透析患者的手腕和脚踝放置电极，电流通过手腕流入身体，经过躯干后从脚踝流出，以获取在某个测试频率下的样本透析患者整体阻抗信息；Obtaining overall impedance information of the sample dialysis patient at multiple test frequencies. Specifically, the test frequency can be within a preset frequency range, for example, within a range of 10 Hz to 100 kHz. Electrodes are placed on the wrists and ankles of the sample dialysis patient. Current flows into the body through the wrists, passes through the trunk, and then flows out from the ankles to obtain overall impedance information of the sample dialysis patient at a certain test frequency.
获取样本透析患者在多种测试频率下的多个测试节段的节段阻抗信息，其中，测试节段可以为上肢、下肢、躯干等；Obtaining segment impedance information of multiple test segments of a sample dialysis patient at multiple test frequencies, wherein the test segment may be an upper limb, a lower limb, a trunk, etc.;
基于样本透析患者在多种测试频率下的整体阻抗信息和多个测试节段的节段阻抗信息，生成样本透析患者的阻抗频率矩阵，其中，阻抗频率矩阵的第一个行向量可以由样本透析患者在多种测试频率下的整体阻抗组成，阻抗频率矩阵的其它行向量可以由样本透析患者的某个测试节段在多种测试频率下的节段阻抗组成。Based on the overall impedance information of the sample dialysis patient at multiple test frequencies and the segment impedance information of multiple test segments, an impedance frequency matrix of the sample dialysis patient is generated, wherein the first row vector of the impedance frequency matrix can be composed of the overall impedance of the sample dialysis patient at multiple test frequencies, and the other row vectors of the impedance frequency matrix can be composed of the segment impedance of a certain test segment of the sample dialysis patient at multiple test frequencies.
数据分析模块可以用于基于多个样本透析患者的基础信息，对多个样本透析患者进行聚类，确定多个样本簇，对于每个样本簇，基于样本簇包括的每个样本透析患者的干体重相关信息，确定样本簇对应的最优阻抗采集位置及最优阻抗采集参数。The data analysis module can be used to cluster multiple sample dialysis patients based on their basic information, determine multiple sample clusters, and for each sample cluster, determine the optimal impedance acquisition position and optimal impedance acquisition parameters corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster.
在一些实施例中，数据分析模块基于多个样本透析患者的基础信息，对多个样本透析患者进行聚类，确定多个样本簇，包括：In some embodiments, the data analysis module clusters the multiple sample dialysis patients based on the basic information of the multiple sample dialysis patients to determine multiple sample clusters, including:
基于任意两个样本透析患者的基础信息，计算任意两个样本透析患者的基础信息相似度；Based on the basic information of any two sample dialysis patients, calculate the similarity of the basic information of any two sample dialysis patients;
基于任意两个样本透析患者的基础信息相似度，对多个样本透析患者进行聚类，确定多个样本簇。Based on the similarity of basic information of any two sample dialysis patients, multiple sample dialysis patients are clustered to determine multiple sample clusters.
具体的，可以通过相似度确定模型基于两个样本透析患者的基础信息，计算两个样本透析患者的基础信息相似度，其中，相似度确定模型可以为卷积神经网络（Convolutional Neural Network,CNN）模型。Specifically, the similarity of the basic information of the two sample dialysis patients can be calculated based on the basic information of the two sample dialysis patients through a similarity determination model, wherein the similarity determination model can be a Convolutional Neural Network (CNN) model.
可以通过K均值聚类算法基于任意两个样本透析患者的基础信息相似度，对多个样本透析患者进行聚类，确定多个样本簇。The K-means clustering algorithm can be used to cluster multiple sample dialysis patients based on the similarity of basic information of any two sample dialysis patients to determine multiple sample clusters.
在一些实施例中，数据分析模块基于样本簇包括的每个样本透析患者的干体重相关信息，确定样本簇对应的最优阻抗采集位置，包括：In some embodiments, the data analysis module determines the optimal impedance acquisition position corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster, including:
基于样本簇包括的每个样本透析患者在多种测试频率下的整体阻抗信息和多个测试节段的节段阻抗信息，计算每个测试节段对应的节段阻抗相关参数；Based on the overall impedance information of each sample dialysis patient at multiple test frequencies and the segment impedance information of multiple test segments included in the sample cluster, the segment impedance related parameters corresponding to each test segment are calculated;
基于样本簇包括的每个样本透析患者在多种测试频率下的多个测试节段的节段阻抗信息，计算每个测试节段对应的节段阻抗相似参数；Based on the segment impedance information of multiple test segments of each sample dialysis patient at multiple test frequencies included in the sample cluster, a segment impedance similarity parameter corresponding to each test segment is calculated;
基于每个测试节段对应的节段阻抗相关参数和节段阻抗相似参数，确定目标节段；Determine the target segment based on the segment impedance related parameters and segment impedance similarity parameters corresponding to each test segment;
基于目标节段，确定样本簇对应的最优阻抗采集位置。Based on the target segment, the optimal impedance acquisition position corresponding to the sample cluster is determined.
具体的，可以基于以下公式计算节段阻抗相关参数：Specifically, the segment impedance related parameters can be calculated based on the following formula:
其中，为第i个测试节段对应的节段阻抗相关参数，为第i个测试节段在第n个样本透析患者的节段阻抗相关参数，为样本簇包括的样本透析患者的总数，为第n个样本透析患者的第i个测试节段在第m个测试频率下的节段阻抗，为测试频率的总数，为第n个样本透析患者在第m个测试频率下的整体阻抗。in, is the segment impedance related parameter corresponding to the i-th test segment, is the segment impedance related parameter of the i-th test segment in the n-th sample dialysis patient, is the total number of sample dialysis patients included in the sample cluster, is the segment impedance of the ith test segment of the nth sample dialysis patient at the mth test frequency, is the total number of test frequencies, is the overall impedance of the nth sample dialysis patient at the mth test frequency.
可以基于以下公式计算节段阻抗相似参数：The segment impedance similarity parameter can be calculated based on the following formula:
其中，为第i个测试节段对应的节段阻抗相似参数，为第e个样本透析患者和第f个样本透析患者在第i个测试节段的相似参数，为第e个样本透析患者的第i个测试节段在第m个测试频率下的节段阻抗，为第f个样本透析患者的第i个测试节段在第m个测试频率下的节段阻抗。in, is the segment impedance similarity parameter corresponding to the i-th test segment, are similar parameters of the e-th sample dialysis patient and the f-th sample dialysis patient in the i-th test segment, is the segment impedance of the i-th test segment of the e-th sample dialysis patient at the m-th test frequency, is the segment impedance of the i-th test segment of the f-th sample dialysis patient at the m-th test frequency.
可以基于每个测试节段对应的节段阻抗相关参数和节段阻抗相似参数，确定每个测试节段的筛选分值，将筛选分值大于预设筛选分值阈值的测试节段作为目标节段。样本簇对应的最优阻抗采集位置包括目标节段。The screening score of each test segment can be determined based on the segment impedance related parameters and segment impedance similarity parameters corresponding to each test segment, and the test segment with a screening score greater than a preset screening score threshold is used as the target segment. The optimal impedance acquisition position corresponding to the sample cluster includes the target segment.
可以基于以下公式计算测试节段的筛选分值：The screening score for a test segment can be calculated based on the following formula:
其中，为第i个测试节段的筛选分值，及为预设权重，且及大于0，为预设参数。in, is the screening score of the i-th test segment, and is the preset weight, and and greater than 0, are preset parameters.
在一些实施例中，数据分析模块基于样本簇包括的每个样本透析患者的干体重相关信息，确定样本簇对应的最优阻抗采集参数，包括：In some embodiments, the data analysis module determines the optimal impedance acquisition parameters corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster, including:
确定样本簇的候选整体阻抗采集频率方案；determining candidate overall impedance acquisition frequency schemes for the sample cluster;
确定样本簇的每个目标节段对应的候选节段阻抗采集频率方案；Determine a candidate segment impedance acquisition frequency scheme corresponding to each target segment of the sample cluster;
基于样本簇的候选整体阻抗采集频率方案和每个目标节段对应的候选节段阻抗采集频率方案，确定样本簇对应的最优阻抗采集参数。Based on the candidate overall impedance acquisition frequency scheme of the sample cluster and the candidate segment impedance acquisition frequency scheme corresponding to each target segment, the optimal impedance acquisition parameters corresponding to the sample cluster are determined.
在一些实施例中，数据分析模块确定样本簇的候选整体阻抗采集频率方案，包括：In some embodiments, the data analysis module determines a candidate overall impedance acquisition frequency scheme for a sample cluster, including:
对于样本簇包括的每个样本透析患者，基于样本透析患者在多种测试频率下的整体阻抗信息，拟合样本透析患者对应的整体阻抗频率测试曲线；For each sample dialysis patient included in the sample cluster, based on the overall impedance information of the sample dialysis patient at multiple test frequencies, an overall impedance frequency test curve corresponding to the sample dialysis patient is fitted;
重复执行对多种测试频率进行抽样，对于样本簇包括的每个样本透析患者，基于样本透析患者在抽样的测试频率下的整体阻抗信息，拟合整体阻抗频率预测曲线，基于整体阻抗频率预测曲线与整体阻抗频率测试曲线之间的相似度，计算整体抽样有效参数，直至满足预设抽样条件，基于每种抽样方案对应的整体抽样有效参数，确定候选整体阻抗采集频率方案。Sampling of multiple test frequencies is performed repeatedly. For each sample dialysis patient included in the sample cluster, an overall impedance frequency prediction curve is fitted based on the overall impedance information of the sample dialysis patient at the sampled test frequency. Based on the similarity between the overall impedance frequency prediction curve and the overall impedance frequency test curve, the overall sampling effective parameters are calculated until the preset sampling conditions are met. Based on the overall sampling effective parameters corresponding to each sampling scheme, the candidate overall impedance acquisition frequency scheme is determined.
具体的，对多种测试频率进行抽样，可以同时抽取三个以上的测试频率。整体阻抗频率预测曲线与整体阻抗频率测试曲线之间的相似度越高，整体抽样有效参数越大，将整体抽样有效参数大于预设整体抽样有效参数阈值的抽样方案包括的抽样的测试频率作为候选整体阻抗采集频率方案。Specifically, sampling of multiple test frequencies may be performed, and more than three test frequencies may be sampled simultaneously. The higher the similarity between the overall impedance frequency prediction curve and the overall impedance frequency test curve, the greater the overall sampling effective parameter, and the sampling test frequencies included in the sampling scheme whose overall sampling effective parameter is greater than the preset overall sampling effective parameter threshold are taken as candidate overall impedance acquisition frequency schemes.
例如，一次抽样中，抽取测试频率包括10 Hz、100 Hz 、30 kHz 、100 kHz，根据样本透析患者在10 Hz、100 Hz 、30 kHz 、100 kHz下的整体阻抗信息，拟合整体阻抗频率预测曲线，基于整体阻抗频率预测曲线与整体阻抗频率测试曲线之间的相似度，计算整体抽样有效参数大于预设整体抽样有效参数阈值，则一个候选整体阻抗采集频率方案为10 Hz、100 Hz 、30 kHz 、100 kHz。For example, in one sampling, the test frequencies include 10 Hz, 100 Hz, 30 kHz, and 100 kHz. According to the overall impedance information of the sample dialysis patients at 10 Hz, 100 Hz, 30 kHz, and 100 kHz, the overall impedance frequency prediction curve is fitted, and based on the similarity between the overall impedance frequency prediction curve and the overall impedance frequency test curve, the overall sampling effective parameter is calculated to be greater than the preset overall sampling effective parameter threshold, then a candidate overall impedance acquisition frequency scheme is 10 Hz, 100 Hz, 30 kHz, and 100 kHz.
可以通过非线性最小二乘法，拟合样本透析患者对应的整体阻抗频率测试曲线和整体阻抗频率预测曲线。The overall impedance frequency test curve and the overall impedance frequency prediction curve corresponding to the sample dialysis patients can be fitted by the nonlinear least square method.
预设抽样条件可以为抽样次数大于预设次数阈值，或者整体抽样有效参数大于预设整体抽样有效参数阈值的抽样方案的数量大于预设数量阈值。The preset sampling condition may be that the number of samplings is greater than a preset number threshold, or the number of sampling schemes whose overall sampling effective parameters are greater than a preset overall sampling effective parameter threshold is greater than a preset number threshold.
在一些实施例中，数据分析模块确定样本簇的每个目标节段对应的候选节段阻抗采集频率方案，包括：In some embodiments, the data analysis module determines a candidate segment impedance acquisition frequency scheme corresponding to each target segment of the sample cluster, including:
对于样本簇包括的每个样本透析患者，基于样本透析患者在多种测试频率下的多个测试节段的节段阻抗信息，拟合样本透析患者的每个目标节段对应的节段阻抗频率测试曲线；For each sample dialysis patient included in the sample cluster, based on the segment impedance information of multiple test segments of the sample dialysis patient at multiple test frequencies, a segment impedance frequency test curve corresponding to each target segment of the sample dialysis patient is fitted;
对于每种目标节段，重复执行对多种测试频率进行抽样，对于样本簇包括的每个样本透析患者，基于样本透析患者在抽样的测试频率下的目标节段的节段阻抗信息，拟合节段阻抗频率预测曲线，基于节段阻抗频率预测曲线与节段阻抗频率测试曲线之间的相似度，计算节段抽样有效参数，直至满足预设抽样条件，基于每种抽样方案对应的节段抽样有效参数，确定目标节段对应的候选节段阻抗采集频率方案。For each target segment, sampling of multiple test frequencies is repeated. For each sample dialysis patient included in the sample cluster, based on the segment impedance information of the target segment of the sample dialysis patient at the sampled test frequency, the segment impedance frequency prediction curve is fitted. Based on the similarity between the segment impedance frequency prediction curve and the segment impedance frequency test curve, the segment sampling effective parameters are calculated until the preset sampling conditions are met. Based on the segment sampling effective parameters corresponding to each sampling scheme, the candidate segment impedance acquisition frequency scheme corresponding to the target segment is determined.
具体的，确定目标节段对应的候选节段阻抗采集频率方案与确定候选整体阻抗采集频率方案的方式相似，此处不再赘述。Specifically, the method of determining the candidate segment impedance acquisition frequency scheme corresponding to the target segment is similar to the method of determining the candidate overall impedance acquisition frequency scheme, which will not be repeated here.
在一些实施例中，可以通过方案确定模型基于候选整体阻抗采集频率方案和每个目标节段对应的候选节段阻抗采集频率方案，确定样本簇对应的最优阻抗采集参数，其中，方案确定模型可以为卷积神经网络（Convolutional Neural Network,CNN）模型，最优阻抗采集参数可以包括多个最优阻抗采集频率。In some embodiments, the optimal impedance acquisition parameters corresponding to the sample cluster can be determined by a scheme determination model based on the candidate overall impedance acquisition frequency scheme and the candidate segment impedance acquisition frequency scheme corresponding to each target segment, wherein the scheme determination model can be a convolutional neural network (CNN) model, and the optimal impedance acquisition parameters can include multiple optimal impedance acquisition frequencies.
在一些实施例中，数据分析模块还用于：基于样本簇包括的每个样本透析患者的干体重相关信息，建立样本簇对应的阻抗修正模型和干体重分析模型，其中，阻抗修正模型可以为深度确定性策略梯度（Deep Deterministic Policy Gradient，DDPG）模型，干体重分析模型可以为卷积神经网络（Convolutional Neural Network,CNN）模型。In some embodiments, the data analysis module is also used to: establish an impedance correction model and a dry weight analysis model corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster, wherein the impedance correction model can be a Deep Deterministic Policy Gradient (DDPG) model, and the dry weight analysis model can be a Convolutional Neural Network (CNN) model.
在一些实施例中，数据分析模块基于样本簇包括的每个样本透析患者的干体重相关信息，建立样本簇对应的阻抗修正模型，包括：In some embodiments, the data analysis module establishes an impedance correction model corresponding to the sample cluster based on the dry weight related information of each sample dialysis patient included in the sample cluster, including:
基于样本簇包括的每个样本透析患者的干体重相关信息，确定每种生理参数与样本簇的相关参数，基于每种生理参数与样本簇的相关参数，确定目标生理参数；Based on the dry weight related information of each sample dialysis patient included in the sample cluster, determining the related parameter of each physiological parameter and the sample cluster, and based on the related parameter of each physiological parameter and the sample cluster, determining the target physiological parameter;
基于样本簇包括的每个样本透析患者的干体重相关信息和目标生理参数，建立样本簇对应的阻抗修正模型。Based on the dry weight related information and target physiological parameters of each sample dialysis patient included in the sample cluster, an impedance correction model corresponding to the sample cluster is established.
具体的，可以通过相关参数确定模型基于样本簇包括的每个样本透析患者的干体重相关信息，确定每种生理参数与样本簇的相关参数，其中，相关参数确定模型为卷积神经网络（Convolutional Neural Network,CNN）模型。Specifically, the relevant parameters of each physiological parameter and the sample cluster can be determined based on the dry weight related information of each sample dialysis patient included in the sample cluster through the relevant parameter determination model, wherein the relevant parameter determination model is a Convolutional Neural Network (CNN) model.
可以将相关参数大于预设相关参数阈值的生理参数作为目标生理参数。A physiological parameter whose relevant parameter is greater than a preset relevant parameter threshold may be used as a target physiological parameter.
成分采集模块可以用于获取待分析透析患者的基础信息，基于待分析透析患者的基础信息，确定目标样本簇，基于目标样本簇对应的最优阻抗采集位置及最优阻抗采集参数，采集待分析透析患者的阻抗信息。The component acquisition module can be used to obtain basic information of the dialysis patients to be analyzed, determine the target sample cluster based on the basic information of the dialysis patients to be analyzed, and acquire the impedance information of the dialysis patients to be analyzed based on the optimal impedance acquisition position and optimal impedance acquisition parameters corresponding to the target sample cluster.
其中，待分析透析患者的阻抗信息可以包括待分析透析患者在多种最优阻抗采集频率下的整体阻抗信息以及待分析透析患者的每个目标节段在多种最优阻抗采集频率下的节段阻抗信息。The impedance information of the dialysis patient to be analyzed may include the overall impedance information of the dialysis patient to be analyzed at multiple optimal impedance acquisition frequencies and the segment impedance information of each target segment of the dialysis patient to be analyzed at multiple optimal impedance acquisition frequencies.
成分采集模块还可以用于采集待分析透析患者的人体成分信息、生理参数信息及标记物水平信息。The component collection module can also be used to collect the body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed.
干体重分析模块可以用于基于待分析透析患者的阻抗信息、人体成分信息、生理参数信息及标记物水平信息，对待分析透析患者的干体重进行分析。The dry weight analysis module can be used to analyze the dry weight of the dialysis patient to be analyzed based on the impedance information, body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed.
在一些实施例中，干体重分析模块基于待分析透析患者的阻抗信息、人体成分信息、生理参数信息及标记物水平信息，对待分析透析患者的干体重进行分析，包括：In some embodiments, the dry weight analysis module analyzes the dry weight of the dialysis patient to be analyzed based on the impedance information, body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed, including:
通过目标样本簇对应的阻抗修正模型，基于待分析透析患者的人体成分信息及生理参数信息，对待分析透析患者的阻抗信息进行修正；The impedance information of the dialysis patients to be analyzed is corrected based on the body composition information and physiological parameter information of the dialysis patients to be analyzed by using the impedance correction model corresponding to the target sample cluster;
通过目标样本簇对应的干体重分析模型，基于修正后的阻抗信息和标记物水平信息，对待分析透析患者的干体重进行分析。The dry weight of the dialysis patients to be analyzed is analyzed based on the corrected impedance information and marker level information through the dry weight analysis model corresponding to the target sample cluster.
图2是本申请一实施例中示出的一种基于人体成分的透析干体重分析方法的流程图，如图2所示，一种基于人体成分的透析干体重分析方法可以包括以下流程。FIG2 is a flow chart of a method for analyzing dialysis dry body weight based on human body composition shown in an embodiment of the present application. As shown in FIG2 , a method for analyzing dialysis dry body weight based on human body composition may include the following process.
步骤210，获取多个样本透析患者的干体重相关信息，其中，干体重相关信息包括基础信息、人体成分信息、生理参数信息、标记物水平信息、阻抗频率矩阵以及干体重信息；Step 210, obtaining information related to dry weight of a plurality of sample dialysis patients, wherein the information related to dry weight includes basic information, human body composition information, physiological parameter information, marker level information, impedance frequency matrix and dry weight information;
步骤220，基于多个样本透析患者的基础信息，对多个样本透析患者进行聚类，确定多个样本簇；Step 220, clustering the multiple sample dialysis patients based on the basic information of the multiple sample dialysis patients to determine multiple sample clusters;
步骤230，对于每个样本簇，基于样本簇包括的每个样本透析患者的干体重相关信息，确定样本簇对应的最优阻抗采集位置及最优阻抗采集参数；Step 230, for each sample cluster, based on the dry weight related information of each sample dialysis patient included in the sample cluster, determine the optimal impedance acquisition position and optimal impedance acquisition parameters corresponding to the sample cluster;
步骤240，获取待分析透析患者的基础信息，基于待分析透析患者的基础信息，确定目标样本簇；Step 240, obtaining basic information of the dialysis patient to be analyzed, and determining a target sample cluster based on the basic information of the dialysis patient to be analyzed;
步骤250，基于目标样本簇对应的最优阻抗采集位置及最优阻抗采集参数，采集待分析透析患者的阻抗信息；Step 250, based on the optimal impedance acquisition position and optimal impedance acquisition parameters corresponding to the target sample cluster, the impedance information of the dialysis patient to be analyzed is collected;
步骤260，采集待分析透析患者的人体成分信息、生理参数信息及标记物水平信息；Step 260, collecting the body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed;
步骤270，基于待分析透析患者的阻抗信息、人体成分信息、生理参数信息及标记物水平信息，对待分析透析患者的干体重进行分析。Step 270: Analyze the dry weight of the dialysis patient to be analyzed based on the impedance information, body composition information, physiological parameter information and marker level information of the dialysis patient to be analyzed.
一种基于人体成分的透析干体重分析方法可以由一种基于人体成分的透析干体重分析系统执行，关于一种基于人体成分的透析干体重分析方法的更多描述可以参见一种基于人体成分的透析干体重分析系统的相关描述，此处不再赘述。A dialysis dry weight analysis method based on human body composition can be performed by a dialysis dry weight analysis system based on human body composition. For more descriptions of a dialysis dry weight analysis method based on human body composition, please refer to the relevant descriptions of a dialysis dry weight analysis system based on human body composition, which will not be repeated here.
最后，应当理解的是，本说明书中所述实施例仅用以说明本说明书实施例的原则。其他的变形也可能属于本说明书的范围。因此，作为示例而非限制，本说明书实施例的替代配置可视为与本说明书的教导一致。相应地，本说明书的实施例不仅限于本说明书明确介绍和描述的实施例。Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.
| Application Number | Priority Date | Filing Date | Title |
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| CN202411084214.1ACN118609802B (en) | 2024-08-08 | 2024-08-08 | Method and system for analyzing dialysis dry weight based on human body components |
| Application Number | Priority Date | Filing Date | Title |
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| CN202411084214.1ACN118609802B (en) | 2024-08-08 | 2024-08-08 | Method and system for analyzing dialysis dry weight based on human body components |
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| CN118609802B CN118609802B (en) | 2024-10-29 |
| Application Number | Title | Priority Date | Filing Date |
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| CN202411084214.1AActiveCN118609802B (en) | 2024-08-08 | 2024-08-08 | Method and system for analyzing dialysis dry weight based on human body components |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030120170A1 (en)* | 2000-08-14 | 2003-06-26 | Fansan Zhu | Device and method for monitoring and controlling physiologic parameters of a dialysis patient using segmental bioimpedance |
| US6615077B1 (en)* | 2000-08-14 | 2003-09-02 | Renal Research Institute, Llc | Device and method for monitoring and controlling physiologic parameters of a dialysis patient using segmental bioimpedence |
| CN112951419A (en)* | 2020-11-11 | 2021-06-11 | 复旦大学附属华山医院 | Hemodialysis dry weight intelligent assessment device |
| CN117198551A (en)* | 2023-11-08 | 2023-12-08 | 天津医科大学第二医院 | Kidney function deterioration pre-judging system based on big data analysis |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030120170A1 (en)* | 2000-08-14 | 2003-06-26 | Fansan Zhu | Device and method for monitoring and controlling physiologic parameters of a dialysis patient using segmental bioimpedance |
| US6615077B1 (en)* | 2000-08-14 | 2003-09-02 | Renal Research Institute, Llc | Device and method for monitoring and controlling physiologic parameters of a dialysis patient using segmental bioimpedence |
| CN112951419A (en)* | 2020-11-11 | 2021-06-11 | 复旦大学附属华山医院 | Hemodialysis dry weight intelligent assessment device |
| CN117198551A (en)* | 2023-11-08 | 2023-12-08 | 天津医科大学第二医院 | Kidney function deterioration pre-judging system based on big data analysis |
| Title |
|---|
| 吴姝焜 等: "人体成分分析仪监测在改善维持性血液透析患者透析低血压中的作用", 中国医药导刊, vol. 18, no. 01, 15 January 2016 (2016-01-15), pages 28 - 29* |
| 张家隆 等: "直接节段多频生物电阻抗分析技术在血液透析患者干体质量评估中的应用", 实用临床医药杂志, vol. 22, no. 13, 8 July 2018 (2018-07-08), pages 1 - 5* |
| Publication number | Publication date |
|---|---|
| CN118609802B (en) | 2024-10-29 |
| Publication | Publication Date | Title |
|---|---|---|
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