本揭示內容是有關於一整合系統，尤其更有關於根據時間軸整合病患的病況資料並進行預測的疾病旅程整合系統。The present disclosure relates to an integrated system, and more particularly to a disease journey integrated system that integrates patient condition data based on a time axis and performs predictions.
傳統上，醫院皆係運用醫療資訊管理系統(Healthcare Information System,HIS)對病患的病歷資料進行管理。醫療資訊管理系統是一種電子式的病歷管理系統，係由醫生在每一次問診、體檢等檢驗程序後，將病患的檢驗資料以及病歷資料輸入電腦儲存於資料庫中。如此，當日後該病患再次就診時，醫生即可在電腦上輸入該病患的個人資料，迅速調閱該病患過往的檢驗資料以及病歷資料。Traditionally, hospitals use the Healthcare Information System (HIS) to manage patients' medical records. The HIS is an electronic medical record management system that allows doctors to input the patient's test data and medical records into a computer and store them in a database after each consultation, physical examination, and other examination procedures. In this way, when the patient visits the doctor again in the future, the doctor can input the patient's personal information on the computer and quickly retrieve the patient's past test data and medical records.
然而，傳統醫療資訊管理系統，病患的各項檢驗資料係根據執行檢驗程序的科別分別儲存於對應科別的資料庫中。由於，不同科別的檢驗資料並未進行整合，因此，當醫師要對病患的病況進行進一步判斷而需要參酌不同檢驗資料時，需要開啟不同科別的資料庫查詢曾作過檢驗，才能充分了解病患的病況或是進一步判斷是否需要執行不同檢驗程序。However, in traditional medical information management systems, each test data of a patient is stored in the database of the corresponding department according to the department that performs the test procedure. Since the test data of different departments are not integrated, when doctors need to refer to different test data to make further judgments on the patient's condition, they need to open the databases of different departments to query the tests that have been performed in order to fully understand the patient's condition or further judge whether different test procedures need to be performed.
因此，對於一種能提供醫生迅速地查看所有資料之整合平台存有需求。Therefore, there is a need for an integrated platform that can provide doctors with a quick view of all data.
本案的一實施態樣係提供一種疾病旅程整合系統，包括：一整合裝置；以及一儲存裝置，耦接該整合裝置，其中該儲存裝置儲存有至少一病患一病歷資料以及複數筆檢驗資料，其中，該整合裝置響應至少一使用者裝置輸入的一病患的身分認證資料，自該儲存裝置的該複數筆檢驗資料中篩選出對應該身分認證資料的一病歷資料以及至少一檢驗資料整合在一病患旅程預測平台上提供給該至少一使用者裝置，其中該病患旅程預測平台至少包括一時間軸，該至少一檢驗資料根據對應的檢驗時間依序設置在該時間軸上。One embodiment of the present case provides a disease journey integration system, comprising: an integration device; and a storage device coupled to the integration device, wherein the storage device stores at least one patient's medical history data and a plurality of test data, wherein the integration device responds to a patient's identity authentication data input by at least one user device, selects a medical history data and at least one test data corresponding to the identity authentication data from the plurality of test data in the storage device, integrates them on a patient journey prediction platform, and provides them to the at least one user device, wherein the patient journey prediction platform at least includes a timeline, and the at least one test data is sequentially arranged on the timeline according to the corresponding test time.
在一些實施例中，該複數筆檢驗資料包括至少一已預約尚未進行檢驗的預約檢驗資料。In some embodiments, the plurality of test data includes at least one scheduled test data that has been scheduled but not yet conducted.
在一些實施例中，整合裝置更包括一處理器以及耦接該處理器的一記憶體，其中該記憶體儲存複數筆電腦可讀取指令。In some embodiments, the integrated device further includes a processor and a memory coupled to the processor, wherein the memory stores a plurality of computer-readable instructions.
在一些實施例中，處理器響應該身分認證資料自該記憶體存取該複數筆電腦可讀取指令中之其中一電腦可讀取指令，以執行一擷取模組的應用程序自該儲存裝置篩選出對應該身分認證資料的該病歷資料以及該至少一檢驗資料。In some embodiments, the processor accesses one of the plurality of computer-readable instructions from the memory in response to the identity authentication data to execute an application of a capture module to filter out the medical record data and the at least one test data corresponding to the identity authentication data from the storage device.
在一些實施例中，處理器更自該記憶體存取該複數筆電腦可讀取指令中其中一電腦可讀取指令，以執行一配置模組的應用程序將該病歷資料以及該至少一檢驗資料整合在該病患旅程預測平台。In some embodiments, the processor further accesses one of the plurality of computer-readable instructions from the memory to execute an application of a configuration module to integrate the medical record data and the at least one test data into the patient journey prediction platform.
在一些實施例中，配置模組的該應用程序更用以將該至少一檢驗資料根據對應的檢驗時間依序設置在該時間軸上。In some embodiments, the application of the configuration module is further used to sequentially set the at least one inspection data on the timeline according to the corresponding inspection time.
在一些實施例中，處理器響應一預測點選指令自該記憶體存取該複數筆電腦可讀取指令中之其中一電腦可讀取指令，以執行一預測模組的應用程序，根據該至少一檢驗資料進行一大數據分析以預測該病患的一健康狀況。In some embodiments, the processor accesses one of the plurality of computer-readable instructions from the memory in response to a prediction click instruction to execute an application of a prediction module to perform a large data analysis based on the at least one test data to predict a health condition of the patient.
在一些實施例中，處理器響應一基因檢測點選指令自該記憶體存取該複數筆電腦可讀取指令中之其中一電腦可讀取指令，以執行一基因檢測模組的應用程序，鑑定該病患的DNA碼。In some embodiments, the processor accesses one of the plurality of computer-readable instructions from the memory in response to a gene detection click instruction to execute an application of a gene detection module to identify the patient's DNA code.
在一些實施例中，整合裝置更包括一通訊元件用以傳送該病患旅程預測平台至該至少一使用者裝置。In some embodiments, the integrated device further includes a communication component for transmitting the patient journey prediction platform to the at least one user device.
在一些實施例中，至少一使用者裝置更包括一顯示元件用以顯示該病患旅程預測平台。In some embodiments, at least one user device further includes a display element for displaying the patient journey prediction platform.
因此，依據本案之技術內容，疾病旅程整合系統所提供的AI病患旅程預測平台上設置有一時間軸，在時間軸上依序標示一病患曾經執行和預計執行的檢驗程序以及對應的檢驗日期，依此，醫生可直接根據時間軸選擇要參酌的檢驗資料，以及判斷是否要執行另外的檢驗程序。此外，本案疾病旅程整合系統更提供一預測模組以及一基因檢測模組，根據病患曾作過的檢驗資料以基因資料進行大數據分析，以預測病患未來可能的疾病，讓病患更容易掌握自身的健康狀況。Therefore, according to the technical content of this case, the AI patient journey prediction platform provided by the disease journey integration system is equipped with a timeline, on which the test procedures that a patient has performed and is expected to perform and the corresponding test dates are marked in sequence, so that doctors can directly select the test data to refer to and determine whether to perform another test procedure based on the timeline. In addition, the disease journey integration system of this case also provides a prediction module and a genetic testing module, which uses genetic data to perform big data analysis based on the test data that the patient has performed to predict the patient's possible future diseases, allowing patients to more easily grasp their own health conditions.
以下將以圖式及詳細敘述清楚說明本案之精神，任何所屬技術領域中具有通常知識者在瞭解本案之實施例後，當可由本案所教示之技術，加以改變及修飾，其並不脫離本案之精神與範圍。The following will clearly illustrate the spirit of the present invention with diagrams and detailed descriptions. After understanding the embodiments of the present invention, any person with ordinary knowledge in the relevant technical field can make changes and modifications based on the techniques taught by the present invention without departing from the spirit and scope of the present invention.
本文之用語只為描述特定實施例，而無意為本案之限制。單數形式如“一”、“這” 、“此” 、“本”以及“該”，如本文所用，同樣也包含複數形式。The terms used herein are only for describing specific embodiments and are not intended to be limiting of the present invention. Singular forms such as "a", "this", "here", "this" and "the" as used herein also include plural forms.
關於本文中所使用之『耦接』或『連接』，均可指二或多個元件或裝置相互直接作實體接觸，或是相互間接作實體接觸，亦可指二或多個元件或裝置相互操作或動作。As used herein, “coupled” or “connected” may refer to direct or indirect physical contact between two or more elements or devices, or mutual operation or action between two or more elements or devices.
關於本文中所使用之『包含』、『包括』、『具有』、『含有』等等，均為開放性的用語，即意指包含但不限於。The words "include", "including", "have", "contain", etc. used in this article are open terms, meaning including but not limited to.
關於本文中所使用之『及/或』，係包括所述事物的任一或全部組合。As used herein, "and/or" includes any or all combinations of the items described.
關於本文中所使用之用詞（terms），除有特別註明外，通常具有每個用詞使用在此領域中、在本案之內容中與特殊內容中的平常意義。某些用以描述本案之用詞將於下或在此說明書的別處討論，以提供本領域技術人員在有關本案之描述上額外的引導。The terms used in this document generally have the ordinary meanings of each term used in this field, in the context of this case and in the specific context, unless otherwise specified. Certain terms used to describe this case will be discussed below or elsewhere in this specification to provide additional guidance to those skilled in the art in describing this case.
由於傳統醫療資訊管理系統，係根據執行檢驗程序的科別將病患的各項檢驗資料分別儲存於對應科別的資料庫中。致使當醫師要參酌檢驗資料來對病患的病況進一步判斷，需要多次開啟不同科別的資料庫進行查詢，對醫師而言相當不便。因此，本案疾病旅程整合系統所提供的平台上更包括有一時間軸，在時間軸上依序標示一病患曾經執行和預計執行的檢驗程序以及對應的檢驗日期，依此，醫生可直接根據時間軸選擇要參酌的檢驗資料，以及判斷是否要執行另外的檢驗程序。此外，本案疾病旅程整合系統更提供一預測模組以及一基因檢測模組，根據病患曾作過的檢驗資料進行大數據分析，以預測病患未來可能的疾病，讓病患更容易掌握自身的健康狀況。Because the traditional medical information management system stores the various test data of patients in the database of the corresponding department according to the department that performs the test procedure. When doctors want to refer to the test data to further judge the patient's condition, they need to open the database of different departments for multiple inquiries, which is very inconvenient for doctors. Therefore, the platform provided by the disease journey integration system in this case also includes a timeline, on which the test procedures that a patient has performed and is expected to perform and the corresponding test dates are marked in sequence. In this way, doctors can directly select the test data to refer to according to the timeline and determine whether to perform another test procedure. In addition, the disease journey integration system in this case also provides a prediction module and a genetic testing module, which conducts big data analysis based on the patient's previous test data to predict the patient's possible future diseases, allowing patients to more easily understand their own health conditions.
請參閱第1圖，為本案一較佳具體實施例之疾病旅程整合系統示意圖。本案的疾病旅程整合系統100主要包括一整合裝置110，以及以無線或有線方式連接此整合裝置110的一儲存裝置120。在一較佳實施例中，儲存裝置120儲存有至少一病患的各項病況資料。在一較佳實施例中，病況資料至少包括檢驗資料以及病歷資料。病歷資料為醫生每一次問診時所紀錄之問診資料。檢驗資料包括但不限制為，抽血檢驗資料、超音波檢驗資料、X光檢驗資料、電腦斷層掃描檢驗資料、核磁共振檢驗資料、病理檢驗資料以及手術資料。在一較佳實施例中，整合裝置110可為一伺服器，用以響應至少一使用者裝置130輸入的一病患身分認證資料，以提供對應此病患的人工智慧(AI)病患旅程預測平台200，如第4圖所示，顯示在此至少一使用者裝置130上。在一較佳實施例中，所輸入的病患身分認證資料為病患的病歷號碼或身分資料。在一較佳實施例中，整合裝置110自儲存裝置120篩選出對應此病患的檢驗資料以及病歷資料整合在AI病患旅程預測平台200上提供給至少一使用者裝置130。在一較佳實施例中，使用者裝置130為醫生專用的使用者裝置，可為具網路功能之手機、具網路功能之平板或是具網路功能之電腦。其中，當至少一使用者裝置130透過網路通訊耦接整合裝置110時，至少一使用者裝置130可傳送一病患身分認證資料至整合裝置110，整合裝置110自儲存裝置120篩選出對應此病患的檢驗資料以及病歷資料並整合在AI病患旅程預測平台200上提供給至少一使用者裝置130，依此，醫師即可在單一的AI病患旅程預測平台200上查詢此病患的各種資料。在一些實施例中，儲存裝置120，可為例如，但不限於隨機存取記憶體（random access memory；RAM）、唯讀記憶體（read only memory；ROM）、快閃記憶體、硬碟或其他可用以儲存資料的儲存裝置。Please refer to Figure 1, which is a schematic diagram of a disease journey integration system of a preferred specific embodiment of the present invention. The disease journey integration system 100 of the present invention mainly includes an integration device 110 and a storage device 120 connected to the integration device 110 in a wireless or wired manner. In a preferred embodiment, the storage device 120 stores various medical data of at least one patient. In a preferred embodiment, the medical data at least includes test data and medical history data. Medical history data is the consultation data recorded by the doctor during each consultation. The test data includes but is not limited to blood test data, ultrasound test data, X-ray test data, computer tomography test data, magnetic resonance imaging test data, pathological test data and surgical data. In a preferred embodiment, the integration device 110 may be a server, which responds to a patient identity authentication data input by at least one user device 130 to provide an artificial intelligence (AI) patient journey prediction platform 200 corresponding to the patient, as shown in FIG. 4, which is displayed on the at least one user device 130. In a preferred embodiment, the input patient identity authentication data is the patient's medical record number or identity information. In a preferred embodiment, the integration device 110 selects the test data and medical record data corresponding to the patient from the storage device 120 and integrates them on the AI patient journey prediction platform 200 to provide to at least one user device 130. In a preferred embodiment, the user device 130 is a user device dedicated to doctors, which can be a mobile phone with network function, a tablet with network function, or a computer with network function. When at least one user device 130 is coupled to the integration device 110 through network communication, at least one user device 130 can transmit a patient identity authentication data to the integration device 110, and the integration device 110 selects the test data and medical history data corresponding to the patient from the storage device 120 and integrates them on the AI patient journey prediction platform 200 to provide to at least one user device 130, so that the doctor can query various data of the patient on the single AI patient journey prediction platform 200. In some embodiments, the storage device 120 may be, for example, but not limited to, a random access memory (RAM), a read only memory (ROM), a flash memory, a hard disk, or other storage devices that can be used to store data.
在一些實施例中，疾病旅程整合系統100還可包括至少一間醫院的醫院伺服器，該醫院伺服器係通過網路系統連接至疾病旅程整合系統100，藉以當病患在醫院中進行門診、體健檢或檢驗檢查等各項醫療程序之後，該醫院伺服器上傳該些程序所得的病歷資料，以更新疾病旅程整合系統100儲存裝置120中此病患的病況資料。依此，可保證本案疾病旅程整合系統100儲存裝置120中之病患的病況資料均為最新的資料。In some embodiments, the disease journey integration system 100 may further include a hospital server of at least one hospital, which is connected to the disease journey integration system 100 through a network system, so that when a patient undergoes various medical procedures such as outpatient visits, physical examinations, or tests in the hospital, the hospital server uploads the medical records obtained by these procedures to update the patient's medical condition data in the storage device 120 of the disease journey integration system 100. In this way, it can be ensured that the patient's medical condition data in the storage device 120 of the disease journey integration system 100 in this case are all the latest data.
請參閱第2圖，為本案一較佳具體實施例之使用者裝置130示意圖。在一些實施例中，使用者裝置130上安裝有一AI病患旅程預測平台200應用程式。此AI病患旅程預測平台200應用程式，配置於疾病旅程整合系統100中供使用者裝置130下載使用。在一實施例中，使用者裝置130包括一輸入元件131、一顯示元件132以及一通訊元件133。其中，使用者裝置130可藉由AI病患旅程預測平台200應用程式透過通訊元件133連線整合裝置110，以將病患的身分認證資料傳至整合裝置110，藉以啟動整合裝置110自儲存裝置120篩選出對應此病患的檢驗資料以及病歷資料並整合在AI病患旅程預測平台200上提供給至少一使用者裝置130，以在顯示元件132上顯示包括此病患檢驗資料以及病歷資料的一AI病患旅程預測平台200。在一實施例中，輸入元件131可為一鍵盤或一滑鼠。在另一些實施例中，輸入元件131可為整合於顯示元件132中的一觸控螢幕。在一實施例中，顯示元件132為一液晶顯示模組、一發光二極體顯示模組或其他類似的平面顯示模組，用以顯示AI病患旅程預測平台200。通訊元件133可為一種包括網路卡、網路連接器及傳輸埠的模組化裝置，但並不以此為限。Please refer to FIG. 2, which is a schematic diagram of a user device 130 of a preferred embodiment of the present invention. In some embodiments, an AI patient journey prediction platform 200 application is installed on the user device 130. The AI patient journey prediction platform 200 application is configured in the disease journey integration system 100 for downloading and using by the user device 130. In one embodiment, the user device 130 includes an input element 131, a display element 132, and a communication element 133. The user device 130 can connect to the integration device 110 through the AI patient journey prediction platform 200 application via the communication element 133 to transmit the patient's identity authentication data to the integration device 110, thereby activating the integration device 110 to filter the test data and medical history data corresponding to the patient from the storage device 120 and integrate them on the AI patient journey prediction platform 200 to provide to at least one user device 130, so as to display an AI patient journey prediction platform 200 including the patient's test data and medical history data on the display element 132. In one embodiment, the input element 131 can be a keyboard or a mouse. In other embodiments, the input element 131 can be a touch screen integrated in the display element 132. In one embodiment, the display element 132 is a liquid crystal display module, a light emitting diode display module or other similar flat display modules for displaying the AI patient journey prediction platform 200. The communication element 133 can be a modular device including a network card, a network connector and a transmission port, but is not limited thereto.
請參閱第3圖，為本案一較佳具體實施例之整合裝置示意圖。在一些實施例中，整合裝置110包括一處理器112、一擷取模組113、一配置模組114、一通訊元件115以及一記憶體116。上述的元件可藉由例如，但不限於匯流排彼此進行通訊。記憶體116配置以至少儲存複數電腦可讀取指令。處理器112電性耦接於記憶體116，配置以自記憶體116存取電腦可讀取指令，以控制整合裝置110中的元件執行AI病患旅程預測平台200的功能。更詳細地說，記憶體116中儲存有至少一指令，AI病患旅程預測平台200即關聯於該至少一指令。處理器112可自記憶體116存取並執行該至少一指令，藉以實施由該至少一指令所界定的應用程序，即擷取模組113以及配置模組114的應用程序，來產生包括一病患檢驗資料以及病歷資料的一AI病患旅程預測平台200。在一較佳實施例中，整合裝置110透過通訊元件115連線使用者裝置130，將包括病患檢驗資料以及病歷資料的AI病患旅程預測平台200傳送至使用者裝置130，以在使用者裝置130的顯示元件132上進行顯示。在一較佳實施例中，通訊元件115可為一種包括網路卡、網路連接器及傳輸埠的模組化裝置，但並不以此為限。在一較佳實施例中，處理器112根據病患的身分認證資料自記憶體116存取至少一指令執行擷取模組113應用程序自儲存裝置120篩選出對應此病患身分認證資料的檢驗資料以及病歷資料。處理器112再自記憶體116存取至少一指令執行配置模組114的應用程序將此病患的檢驗資料以及病歷資料整合在一AI病患旅程預測平台200上，並透過通訊元件115傳送至使用者裝置130。Please refer to Figure 3, which is a schematic diagram of an integrated device of a preferred specific embodiment of the present invention. In some embodiments, the integrated device 110 includes a processor 112, a capture module 113, a configuration module 114, a communication element 115, and a memory 116. The above-mentioned components can communicate with each other by, for example, but not limited to, a bus. The memory 116 is configured to store at least a plurality of computer-readable instructions. The processor 112 is electrically coupled to the memory 116 and is configured to access computer-readable instructions from the memory 116 to control the components in the integrated device 110 to execute the functions of the AI patient journey prediction platform 200. In more detail, at least one instruction is stored in the memory 116, and the AI patient journey prediction platform 200 is associated with the at least one instruction. The processor 112 can access and execute the at least one instruction from the memory 116 to implement the application defined by the at least one instruction, that is, the application of the capture module 113 and the configuration module 114, to generate an AI patient journey prediction platform 200 including a patient test data and medical history data. In a preferred embodiment, the integration device 110 is connected to the user device 130 through the communication element 115, and the AI patient journey prediction platform 200 including the patient test data and medical history data is transmitted to the user device 130 for display on the display element 132 of the user device 130. In a preferred embodiment, the communication element 115 can be a modular device including a network card, a network connector and a transmission port, but is not limited thereto. In a preferred embodiment, the processor 112 accesses at least one instruction from the memory 116 to execute the capture module 113 application program according to the patient's identity authentication data to filter the test data and medical history data corresponding to the patient's identity authentication data from the storage device 120. The processor 112 then accesses at least one instruction from the memory 116 to execute the configuration module 114 application program to integrate the patient's test data and medical history data on an AI patient journey prediction platform 200, and transmits them to the user device 130 through the communication element 115.
第4圖所示為本案之一較佳具體實施例之AI病患旅程預測平台200示意圖。在一較佳實施例中，AI病患旅程預測平台200至少包括一時間軸210，用以依序顯示一病患的多個檢驗資料。在一較佳實施例中，當使用者裝置130藉由AI病患旅程預測平台200應用程式連線整合裝置110，並將欲查詢的一病患身分認證資料傳至整合裝置110後，處理器112即會根據此病患的身分認證資料執行擷取模組113應用程序以自儲存裝置120篩選出對應此病患身分認證資料的檢驗資料以及病歷資料。接著，處理器112再執行配置模組114的應用程序將此病患的檢驗資料根據檢驗時間依序配置在此時間軸210上，同時和對應檢驗資料內容設定連接，依此，醫師可直接點時間軸210上顯示的病患檢驗資料查詢內容。在一實施例中，處理器112會響應此點選訊號，根據設定的連接關係將對應病患檢驗資料透過通訊元件115傳送至使用者裝置130。FIG. 4 is a schematic diagram of an AI patient journey prediction platform 200 of a preferred embodiment of the present invention. In a preferred embodiment, the AI patient journey prediction platform 200 includes at least a time axis 210 for sequentially displaying a plurality of test data of a patient. In a preferred embodiment, when the user device 130 connects to the integration device 110 through the AI patient journey prediction platform 200 application and transmits a patient identity authentication data to be queried to the integration device 110, the processor 112 executes the capture module 113 application according to the patient's identity authentication data to filter out the test data and medical history data corresponding to the patient's identity authentication data from the storage device 120. Then, the processor 112 executes the application of the configuration module 114 to sequentially configure the patient's test data on the time axis 210 according to the test time, and simultaneously sets a connection with the corresponding test data content, so that the doctor can directly click on the patient's test data displayed on the time axis 210 to query the content. In one embodiment, the processor 112 will respond to the click signal and transmit the corresponding patient's test data to the user device 130 through the communication element 115 according to the set connection relationship.
在一較佳實施例中，AI病患旅程預測平台200所顯示的資料，包括但不限制於，此病患病歷號碼201、病患的個人資料202以及病患所罹患之疾病資料203，包括疾病名稱、就醫紀錄、家族史等。若此病患於診治此疾病過程中，曾於2023/07/01進行抽血檢驗以及超音波檢驗，2023/07/15進行抽血檢驗、超音波檢驗以及電腦斷層掃描檢驗，2023/08/01進行抽血檢驗、超音波檢驗、病理檢驗以及手術，以及手術後的抽血檢驗、超音波檢驗， 2023/08/12進行抽血檢驗、超音波檢驗以及電腦斷層掃描檢驗。處理器112即會根據此病患的身分認證資料執行擷取模組113應用程序自儲存裝置120篩選出上述資料，處理器112再執行配置模組114的應用程序，以將上述資料根據檢驗時間依序配置在此時間軸210的2023/07/01、2023/07/15、2023/08/01以及2023/08/12的對應位置上。依此，醫生除了可透過AI病患旅程預測平台200上的時間軸210了解病患過往曾做過之檢驗，更可直接知悉檢驗是在何時所做，進一步決定哪一檢驗資料已經不準確而須重新執行檢驗。在其他實施例中，若有新預約檢驗程序，配置模組114亦可根據已預約的檢驗時間或手術將其配置在此時間軸210上，據此醫生可全面了解此病患未來的醫療內容，且醫生可直接點選時間軸210上顯示的檢驗名稱，處理器112響應此點選訊號，根據配置模組114設定的連接關係將對應病患的檢驗資料透過通訊元件115傳送至使用者裝置130。In a preferred embodiment, the data displayed by the AI patient journey prediction platform 200 includes but is not limited to the patient's medical record number 201, the patient's personal information 202, and the patient's disease data 203, including the name of the disease, medical records, family history, etc. If the patient had a blood test and an ultrasound test on 2023/07/01, a blood test, an ultrasound test, and a CT scan on 2023/07/15, a blood test, an ultrasound test, a pathological test, and surgery on 2023/08/01, and a blood test and an ultrasound test after the surgery, and a blood test, an ultrasound test, and a CT scan on 2023/08/12 during the diagnosis and treatment of the disease. The processor 112 will execute the capture module 113 application program from the storage device 120 to filter the above data based on the patient's identity authentication data, and then execute the configuration module 114 application program to sequentially configure the above data at the corresponding positions of 2023/07/01, 2023/07/15, 2023/08/01, and 2023/08/12 on the time axis 210 according to the test time. In this way, in addition to understanding the tests that the patient has done in the past through the time axis 210 on the AI patient journey prediction platform 200, the doctor can also directly know when the test was done, and further determine which test data is inaccurate and needs to be re-tested. In other embodiments, if there is a new scheduled test procedure, the configuration module 114 can also configure it on this timeline 210 according to the scheduled test time or surgery, so that the doctor can fully understand the future medical content of the patient, and the doctor can directly click on the test name displayed on the timeline 210. The processor 112 responds to the click signal and transmits the corresponding patient's test data to the user device 130 through the communication element 115 according to the connection relationship set by the configuration module 114.
在另一實施例中，整合裝置110更包括一預測模組117，並於AI病患旅程預測平台200上設置有一對應控制鈕(圖中未繪示出)。處理器112可響應點選此控制鈕的點選指令自記憶體116存取並執行至少一指令，以實施預測模組117的應用程序，來根據病患檢驗資料進行大數據分析以預測此病患的健康狀況。在一較佳實施例中，預測模組117會擷取患者的所有檢測資料進行預測。In another embodiment, the integrated device 110 further includes a prediction module 117, and a corresponding control button (not shown) is provided on the AI patient journey prediction platform 200. The processor 112 can access and execute at least one instruction from the memory 116 in response to a click instruction of clicking the control button to implement the application of the prediction module 117 to perform big data analysis based on the patient's test data to predict the patient's health condition. In a preferred embodiment, the prediction module 117 will capture all the patient's test data for prediction.
在另一較佳實施例中，整合裝置110更包括一基因檢測模組118用以鑑定患者的DNA碼，藉以了解基因或染色體是否異常，幫助患者瞭解自身是否有罹患遺傳疾病的風險。於AI病患旅程預測平台200上設置有一對應基因檢測模組118的控制鈕(圖中未繪示出)。處理器112可響應點選此控制鈕的點選指令在一實施例中，處理器112可自記憶體116存取並執行至少一指令，以實施基因檢測模組118的應用程序，鑑定患者的DNA碼。In another preferred embodiment, the integrated device 110 further includes a gene detection module 118 for identifying the patient's DNA code to understand whether the gene or chromosome is abnormal and to help the patient understand whether he or she is at risk of contracting a genetic disease. A control button corresponding to the gene detection module 118 is provided on the AI patient journey prediction platform 200 (not shown in the figure). The processor 112 can respond to a click instruction of clicking this control button. In one embodiment, the processor 112 can access and execute at least one instruction from the memory 116 to implement the application of the gene detection module 118 to identify the patient's DNA code.
綜上所述，本案的疾病旅程整合系統所提供的AI病患旅程預測平台上設置有一時間軸，在時間軸上依序標示一病患曾經執行和預計執行的檢驗程序以及對應的檢驗日期，依此，醫生可直接根據時間軸選擇要參酌的檢驗資料，以及判斷是否要執行另外的檢驗程序。此外，本案疾病旅程整合系統更提供一預測模組以及一基因檢測模組，根據病患曾作過的檢驗資料以基因資料進行大數據分析，以預測病患未來可能的疾病，讓病患更容易掌握自身的健康狀況。In summary, the AI patient journey prediction platform provided by the disease journey integration system in this case is equipped with a timeline, on which the test procedures that a patient has performed and is expected to perform and the corresponding test dates are marked in sequence. Thus, doctors can directly select the test data to be referred to according to the timeline, and determine whether to perform another test procedure. In addition, the disease journey integration system in this case also provides a prediction module and a gene testing module, which uses big data analysis based on the test data that the patient has performed to predict the patient's possible future diseases, so that patients can more easily grasp their own health conditions.
雖然本案以實施例揭露如上，然其並非用以限定本案，任何熟習此技藝者，在不脫離本案之精神和範圍內，當可作各種之更動與潤飾，因此本案之保護範圍當視後附之申請專利範圍所界定者為準。Although the present invention is disclosed as above by way of embodiments, it is not intended to limit the present invention. Anyone skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of the patent application attached hereto.
100:疾病旅程整合系統 110:整合裝置 112:處理器 113:擷取模組 114:配置模組 115:通訊元件 116:記憶體 117:預測模組 118:基因檢測模組 120:儲存裝置 130:使用者裝置 131:輸入元件 132:顯示元件 133:通訊元件 200:人工智慧病患旅程預測平台 201:病歷號碼 202:個人資料 203:疾病資料 210:時間軸100: Disease journey integration system110: Integration device112: Processor113: Capture module114: Configuration module115: Communication component116: Memory117: Prediction module118: Gene detection module120: Storage device130: User device131: Input component132: Display component133: Communication component200: Artificial intelligence patient journey prediction platform201: Medical record number202: Personal information203: Disease data210: Timeline
此處的附圖被併入說明書中並構成本說明書的一部分，這些附圖示出了符合本新型的實施例，並與說明書一起用於說明本新型實施例的技術方案。 第1圖為本案一較佳具體實施例之整和系統示意圖。 第2圖為本案一較佳具體實施例之使用者裝置示意圖。 第3圖為本案一較佳具體實施例之整合裝置示意圖。 第4圖為本案之一較佳具體實施例之AI病患旅程預測平台示意圖。The figures herein are incorporated into the specification and constitute a part of the specification. These figures illustrate embodiments consistent with the present invention and are used together with the specification to illustrate the technical solutions of the embodiments of the present invention.Figure 1 is a schematic diagram of the integrated system of a preferred specific embodiment of the present invention.Figure 2 is a schematic diagram of the user device of a preferred specific embodiment of the present invention.Figure 3 is a schematic diagram of the integrated device of a preferred specific embodiment of the present invention.Figure 4 is a schematic diagram of the AI patient journey prediction platform of a preferred specific embodiment of the present invention.
100:疾病旅程整合系統100: Disease Journey Integration System
110:整合裝置110:Integrated device
120:儲存裝置120: Storage device
130:使用者裝置130: User device
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