WO2022099668A1 - 一种基于家族遗传病与体征数据关联的精准健康管理与风险预警方法及系统 - Google Patents

一种基于家族遗传病与体征数据关联的精准健康管理与风险预警方法及系统 Download PDF

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WO2022099668A1
WO2022099668A1 PCT/CN2020/128908 CN2020128908W WO2022099668A1 WO 2022099668 A1 WO2022099668 A1 WO 2022099668A1 CN 2020128908 W CN2020128908 W CN 2020128908W WO 2022099668 A1 WO2022099668 A1 WO 2022099668A1
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disease
information
database
early warning
abnormal
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PCT/CN2020/128908
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English (en)
French (fr)
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吉桂宜
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四川大学华西医院
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Priority to PCT/CN2020/128908 priority Critical patent/WO2022099668A1/zh
Priority to CN202080081531.1A priority patent/CN114766057A/zh
Publication of WO2022099668A1 publication Critical patent/WO2022099668A1/zh

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

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  • the invention relates to the fields of computer system development and data artificial intelligence, and more particularly, to a method and system for precise health management and risk early warning based on the association of family genetic disease and sign data.
  • Products such as sphygmomanometers or blood glucose meters are already available on the market for users to manage their own health. However, their functions are limited and can only generate the detected blood pressure or blood sugar values, and cannot generate the health related to most organs of the human body. status report. To get a more complete health status report, you need to go to a medical unit such as a hospital or clinic for a health check in person. In addition, in terms of disease diagnosis, the hospital's medical resources are tight, which increases the difficulty of seeing a doctor. How to quickly and accurately assist doctors in diagnosis and follow-up to observe the physical condition of patients have become urgent problems.
  • Health guidance under risk assessment is an important tool for domestic and foreign research in recent years to improve national fitness and prevent diseases, especially in predicting disease risks and personalizing health management and guidance.
  • Some diseases are closely related to familial genetic diseases, but these diseases lack good health management.
  • Some diseases are basically discovered at an advanced stage, and early detection and early treatment of diseases cannot be achieved. Therefore, comprehensive analysis and timely warning of abnormal conditions through the health management system are possible in the era of Internet big data. Combined with the mature application of smart wearable early warning devices, it is very important to achieve comprehensive and accurate assessment of genetic factors and physical indicators, regular monitoring, effective intervention and prevention, and early clinical diagnosis and treatment.
  • the purpose of the present invention is to provide a health early warning method and a health early warning system, which are used to solve the defect that the existing medical system cannot monitor and give early warning of individual disease risks.
  • the present invention provides a health early warning system, including: a database system, the database system at least includes a human body sign database, a disease and abnormal sign association database; a comparison unit for comparing the difference between the human body sign data and the normal index range , and output the abnormal index information; the matching unit matches possible diseases in the disease-abnormal sign association database according to the abnormal sign index information output by the comparison unit, and calculates the matching degree according to the matching situation between the abnormal index information and the disease-related abnormal index
  • the early warning unit according to the matching degree information, carries out early warning for the diseases whose matching degree exceeds the set threshold; the display unit is used to display the disease and matching degree information and early warning information output by the matching unit;
  • the comparison unit is connected with the human body sign database; the matching unit is connected with the comparison unit and the disease-related database respectively; the early warning unit is connected with the comparison unit or the matching unit; and the display unit is connected with the early warning unit.
  • the human body signs include but are not limited to pulse wave data, body temperature data, heart rate data, blood pressure data, blood sugar data, blood oxygen data, cholesterol data, uric acid data, and the like.
  • the human body signs are collected by a collection device, and the collection device can be a portable wearable device or a hospital detection device.
  • the database of the health warning system is stored in a cloud server.
  • the display unit performs sorting and display according to the size of the matching degree. Preferably, it is displayed in descending order of matching degree, displayed according to the degree of risk of the disease, or displayed by classification according to the type of the disease.
  • the human body sign database records the historical sign data records of the human body
  • the display unit also outputs the historical data change information of the abnormal index associated with the early warning disease, preferably, the historical data change of the abnormal index is displayed in the form of a statistical trend graph. trend.
  • the calculation formula of the matching degree is:
  • i represents the abnormal index number
  • j represents the disease serial number
  • P j represents the risk matching degree of disease j
  • factor i represents the index value of abnormal index i
  • f s represents the reference value
  • f sL represents the lower limit of the reference value
  • f sH represents the upper limit of the reference value.
  • the database system also includes a disease-related database; the early-warning unit is connected to the disease-related database, and when the early-warning unit issues an early-warning to a certain disease or diseases, the early-warning unit also calls the disease-related database, and associates the disease with the disease-related database.
  • the disease-related information includes, but is not limited to, the age of onset of the disease, the characteristics of the lesion, disease prevention, knowledge of disease diagnosis and treatment, precautions for the disease (such as diet), medical guidance and other information.
  • the database system also includes a personal medical record database and a family genetic disease information database.
  • the personal medical record database is used to record the basic identity information and historical medical treatment information of the individual, and the family genetic disease information database is used to record the family genetic disease information of the individual; the family genetic disease information database is associated with the disease and abnormal signs
  • the database is associated with the disease association database, and the abnormal sign index information of the family genetic disease and the association information of the disease are obtained. The information is correlated to judge the risk of familial genetic disease, and the judgment result is output to the early warning unit.
  • the health early warning system further includes a warning effect feedback unit and an adaptive adjustment unit, and the adaptive adjustment unit adaptively feedbacks and adjusts the matching degree according to the statistical information of the feedback unit of the early warning effect, thereby improving the availability of the warning. reliability.
  • the early warning effect feedback unit is connected with the individual disease examination database, and is used for obtaining the conclusions obtained from the follow-up examination of early warning diseases.
  • the present invention provides a health warning method, comprising:
  • the matching degree calculation formula is:
  • f s (f sL +f sH )/2, where i represents the abnormal index number, j represents the disease serial number; P j represents the risk matching degree of disease j; Represents the weight coefficient of each abnormal index of a certain disease j; factor i represents the index value of abnormal index i, f s represents the reference value, f sL represents the lower limit of the reference value, and f sH represents the upper limit of the reference value;
  • the database system also includes a personal medical record database and a family genetic disease information database.
  • the personal medical record database is used to record the basic identity information and historical medical treatment information of individuals.
  • the family genetic disease information database is associated with the disease and abnormal sign association database and the disease association database, and the abnormal sign index information of the family genetic disease and the association information of the disease are obtained, at least according to The age of onset and/or lesion characteristic information in the disease association information is associated with the personal age and historical diagnosis record information in the personal medical record database to judge the risk of family genetic disease, and the judgment result is output to the early warning unit;
  • the early warning unit When an early warning is issued for one or more diseases, the early warning unit also calls the disease association database, and outputs the disease association information according to the disease association database; the disease association information includes but is not limited to the disease onset age, lesion characteristics, Disease prevention, knowledge of disease diagnosis and treatment, precautions for disease, medical guidance.
  • It also includes a display step for displaying disease and matching degree information and early warning information, the display step is performed on the terminal device, and the matching and early warning can be completed in the cloud;
  • the risk level of the disease is displayed or classified and displayed according to the type of the disease;
  • the display step also displays the historical data change information of the abnormal indicators associated with the early warning disease, and displays the historical data change trend of the abnormal indicators in the form of a statistical trend chart.
  • the early warning effect feedback unit is connected to the individual disease inspection database, and is used to obtain the conclusion obtained from the follow-up inspection of the early warning disease.
  • the self-adaptive adjustment unit is based on the statistical information of the early warning effect feedback unit. Matching degree, thereby improving the credibility of early warning.
  • the present invention has the following beneficial effects: it can monitor the abnormal data of the individual's sign data and correlate with the abnormality of the disease's sign data, and calculate the matching degree according to the number of indicators and abnormal values, and according to The matching degree is used to carry out the risk warning of the disease, and at the same time, the present invention can also monitor the family genetic disease, to maximize the early warning of the occurrence risk of the family disease, to achieve early diagnosis and early treatment, and to predict the disease risk and personalize health management and guidance. aspect is of great significance.
  • FIG. 1 is a schematic diagram of a health warning system in an embodiment
  • Fig. 2 is a schematic diagram of another health warning system in the embodiment
  • FIG. 3 is a schematic diagram of terminal early warning display information of the health early warning system in the embodiment
  • FIG. 4 is a schematic flowchart of the health warning method in the embodiment
  • a health early warning system includes: a database system, the database system at least includes a human body sign database, a disease and abnormal sign association database; a comparison unit, used for comparing the difference between the human body sign data and the normal index range, and output abnormal index information; the matching unit matches possible diseases in the disease-abnormal sign association database according to the abnormal sign index information output by the comparison unit, and calculates the matching degree according to the matching situation between the abnormal index information and the disease-related abnormal index; an early warning unit, for early warning of diseases whose matching degree exceeds a set threshold according to the matching degree information; a display unit for displaying the diseases and matching degree information and early warning information output by the matching unit;
  • the comparison unit is connected with the human body sign database; the matching unit is connected with the comparison unit and the disease-related database respectively; the early warning unit is connected with the comparison unit or the matching unit; and the display unit is connected with the early warning unit.
  • the human body signs include but are not limited to pulse wave data, body temperature data, heart rate data, blood pressure data, blood glucose data, blood oxygen data, cholesterol data, uric acid data, and the like.
  • the human body signs are collected by a collection device, and the collection device may be a portable wearable device or a hospital detection device.
  • the database of the health warning system is stored in a cloud server.
  • the display unit performs sorting and display according to the size of the matching degree. Preferably, it is displayed in descending order of matching degree, displayed according to the degree of risk of the disease, or displayed by classification according to the type of the disease.
  • the human body sign database records the historical sign data records of the human body
  • the display unit also outputs the historical data change information of the abnormal index associated with the early warning disease, preferably, the historical data change of the abnormal index is displayed in the form of a statistical trend graph. trend.
  • the calculation formula of the matching degree is:
  • i represents the abnormal index number
  • j represents the disease serial number
  • P j represents the risk matching degree of disease j
  • factor i represents the index value of abnormal index i
  • f s represents the reference value
  • f sL represents the lower limit of the reference value
  • f sH represents the upper limit of the reference value.
  • fs takes the median of fsL and fsH .
  • a health early warning system includes: a database system, the database system at least includes a human body sign database, a disease and abnormal sign association database, a personal medical record database, and a family genetic disease an information database, a disease association database; a comparison unit, used to compare the difference between the human body sign data and the normal index range, and output abnormal index information; a matching unit, according to the abnormal sign index information output by the comparison unit, in the disease and abnormal signs association database It matches possible diseases in the middle, and calculates the matching degree according to the matching situation between the abnormal index information and the disease-related abnormal indicators; the early warning unit, according to the matching degree information, warns the diseases whose matching degree exceeds the set threshold; the display unit is used to display the matching Disease and matching information and early warning information output by the unit;
  • the comparison unit is connected with the human body sign database; the matching unit is connected with the comparison unit and the disease-related database respectively; the early warning unit is connected with the comparison unit or the matching unit; the display unit is connected with the early warning unit;
  • the unit is connected with the disease association database, and when the early warning unit issues an alarm for a certain disease or diseases, the early warning unit also calls the disease association database, and outputs the association information of the disease according to the disease association database; the association information of the disease Including but not limited to the age of onset of the disease, the characteristics of the lesion, disease prevention, knowledge of disease diagnosis and treatment, precautions for the disease (such as diet), medical guidance and other information;
  • the family genetic disease information database is associated with the disease and abnormal sign association database and the disease association database, and the abnormal sign index information of the family genetic disease and the association information of the disease are obtained.
  • Information such as personal age and historical diagnosis record information in the personal medical record database to determine the risk of family genetic disease, and output the judgment result to the early warning unit;
  • the personal medical record database is used to record the basic identity information and historical medical treatment information of the individual
  • the family genetic disease information database is used to record the family genetic disease information of the individual.
  • the functional module for providing disease-related information in the disease-related database and the early-warning functional module for familial diseases formed by the personal medical record database, the family disease database, and the disease-abnormal sign association database can exist separately, and are carried out in the system as required. configuration.
  • the health early warning system further includes a warning effect feedback unit and an adaptive adjustment unit, and the adaptive adjustment unit adaptively feedbacks and adjusts the matching degree according to the statistical information of the feedback unit of the early warning effect, thereby improving the availability of the warning. reliability.
  • the early warning effect feedback unit is connected with the individual disease examination database, and is used for obtaining the conclusions obtained from the follow-up examination of early warning diseases.
  • FIG. 3 it is an example of a personal health risk early warning system displayed on a display unit on a mobile terminal.
  • the display unit can display the name and serial number of the individual; in addition, the display unit also displays the diseases whose matching degree exceeds a certain set threshold. Preferably, different thresholds are set for different disease types.
  • the diseases are sorted according to the matching degree, and the diseases with different risk levels are displayed in different colors, such as the small triangles with different colors in the figure.
  • the display unit can also display various abnormal indicators, and at the same time can query the historical change trend diagram of an abnormal indicator.
  • the display unit there are modules such as disease knowledge, disease prevention, healthy diet, physical examination information, medical guidance, disease diagnosis and treatment, etc. You can click to enter the relevant modules to view as needed.
  • the system also has a one-click reporting function to display risk warning information in a report format.
  • the output mode may be in PDF format.
  • a method of health warning including:
  • Step S1 sending the human body sign data collected by the collection device to the human body sign database on the cloud server side;
  • Step S2 compare the difference between the human body sign data and the normal index range, and output abnormal index information
  • Step S3 matching possible diseases in the disease-abnormal sign association database according to the abnormal index information, and calculating the matching degree according to the matching situation between the abnormal index information and the disease-related abnormal index;
  • step S4 an early warning is performed for diseases whose matching degree exceeds the set threshold.
  • the calculation formula of the matching degree is:
  • i represents the abnormal index number
  • j represents the disease serial number
  • P j represents the risk matching degree of disease j
  • factor i represents the index value of abnormal index i
  • f s represents the reference value
  • f sL represents the lower limit of the reference value
  • f sH represents the upper limit of the reference value.
  • fs takes the median of fsL and fsH .
  • the method of the present invention further includes a display step for displaying disease and matching degree information and early warning information.
  • the displaying step is performed on a terminal device, and the matching and early warning can be completed in the cloud.
  • the body signs are collected by a collection device, and the collection device may be a portable wearable device or a hospital detection device.
  • the above health warning method before sending the human body sign data collected by the collection device to the cloud server, further includes: judging whether the body sign data collected by the collection device is valid; if the body sign data is valid, executing the The step of sending the body sign data to the cloud server, wherein the body signs include but are not limited to pulse wave data, body temperature data, heart rate data, blood pressure data, blood sugar data, blood oxygen data, cholesterol data, uric acid data, etc. .
  • the early warning unit when an early warning is issued for one or more diseases, the early warning unit also calls the disease association database, and outputs disease association information according to the disease association database.
  • the disease-related information includes disease onset age, lesion characteristics, disease prevention, disease diagnosis and treatment knowledge, precautions for disease (such as diet), medical guidance and other information.
  • the display unit performs sorting and display according to the size of the matching degree. Preferably, it is displayed in descending order of matching degree, displayed according to the degree of risk of the disease, or displayed by classification according to the type of the disease.
  • the human body sign database records the historical sign data records of the human body
  • the display step also displays the historical data change information of the abnormal indicators associated with the early warning disease, preferably, the historical data change trend of the abnormal indicators is displayed in the form of a statistical trend graph.
  • the present invention also includes the steps of acquiring and displaying disease-related information
  • the early-warning unit is connected to the disease-related database, and when the early-warning unit issues an early-warning for one or more diseases, the early-warning unit also calls the disease-related information.
  • the association database and according to the disease association database, the disease association information is output.
  • the disease-related information includes, but is not limited to, the age of onset of the disease, the characteristics of the lesion, disease prevention, knowledge of disease diagnosis and treatment, precautions for the disease (such as diet), medical guidance and other information.
  • the database system further includes a personal medical record database and a family genetic disease information database, the personal medical record database is used to record the basic identity information and historical medical treatment information of the individual, and the family genetic disease information database is used to record the family genetic disease information of the individual.
  • the family genetic disease information database is associated with the disease and abnormal sign association database and the disease association database, and the abnormal sign index information of the family genetic disease and the association information of the disease are obtained. and other information, correlate with the personal age and historical diagnosis record information in the personal medical record database to judge the risk of familial genetic disease, and output the judgment result to the early warning unit.
  • the present invention also includes the steps of early warning effect feedback and self-adaptive adjustment.
  • the self-adaptive adjusting unit adjusts the matching degree by self-adaptive feedback according to the statistical information of the early warning effect feedback unit, thereby improving the credibility of the early warning. .
  • an individual disease examination database is also included, which is used to record the relevant examinations and images performed by the individual to further confirm the disease, including the conclusions obtained by doctors or artificial intelligence systems.
  • the early warning effect feedback unit is connected with the individual disease examination database, and is used for obtaining the conclusions obtained from the follow-up examination of early warning diseases.

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Abstract

一种健康预警系统，包括：数据库系统，至少包括人体体征数据库、疾病与异常体征关联数据库；比较单元，用于比较人体体征数据与正常指标范围的差异，并输出异常指标信息；匹配单元，根据比较单元输出的异常体征指标信息在所述疾病与异常体征关联数据库中匹配可能的疾病，并根据异常指标信息与疾病关联异常指标的匹配情况计算匹配度；预警单元，根据匹配度信息，对于匹配度超过设定阈值的疾病进行预警；显示单元，用于显示匹配单元输出的疾病与匹配度信息以及预警信息；此外，该系统还对家族病风险预警，可用于解决现有医疗体系无法对个人疾病及家族病发病早期风险进行监控和预警的缺陷。

Description

一种基于家族遗传病与体征数据关联的精准健康管理与风险预警方法及系统 技术领域
本发明涉及计算机系统开发及数据人工智能领域，更具体地，涉及一种基于家族遗传病与体征数据关联的精准健康管理与风险预警方法及系统。
背景技术
随着社会经济的发展，人们对自身健康的关注也更为突出，亚健康人群基数也逐年增大，并且呈现出年轻化的趋势，能够提前预判自身健康问题并提前采取措施成为个人健康和公共健康的重要诉求。
市面上已有例如血压计或血糖计等产品可供使用者进行自主健康管理，然而其功能有限，仅能产生所检测到的血压值或血糖值，并不能产生与人体大部分器官有关的健康状态报告。若要得到较完整的健康状态报告，则需亲自到例如医院或诊所等医疗单位进行健康检查。此外，在疾病诊断上，医院医疗资源紧张，这增加了看病困难度，如何快速、准确的辅助医生诊断以及后续跟踪观察病人身体状况都成为急需解决的问题。
风险评估下的健康指导是近年来国内外研究提升国民体质与防治疾病的重要工具，特别在预测疾病危险和个性化健康管理及指导方面具有重要的意义。一些疾病与家族遗传病密切相关，然而这些疾病却缺乏良好的健康管理，某些疾病被发现时基本是晚期，未能做到疾病的早发现，早治疗。因此，通过健康管理系统对异常状况的综合分析与及时预警，在互联网大数据时代成为可能。结合智能可穿戴预警设备的成熟应用，实现全面针对遗传因素与体征指标的精准评估、定期监测、有效干预及防控、早期临床诊疗等内容，至关重要。
发明内容
有鉴于此，本发明的目的在于提供健康预警方法及健康预警系统，用于解决现有医疗体系无法对个人疾病风险进行监控和预警的缺陷。
第一方面，本发明提供一种健康预警系统，包括：数据库系统，所述数据库系统至少包括人体体征数据库、疾病与异常体征关联数据库；比较单元，用于比较人体体征数据与正常指标范围的差异，并输出异常指标信息；匹配单元，根据比较单元输出的异常体征指标信息在所述疾病与异常体征关联数据库中匹配可能的疾病，并根据异常指标信息与疾病关联异常指标的匹配情况计算匹配度；预警单元，根据匹配度信息，对于匹配度超过设定阈值的疾病进行预警；显示单元，用于显示匹配单元输出的疾病与匹配度信息以及预警信息；
其中，比较单元与人体体征数据库相连；匹配单元分别与所述比较单元和所述疾病关联数据库连接；预警单元与所述比较单元或所述匹配单元连接；显示单元与所述预警单元连接。
所述人体体征包括但不限于脉波数据、体温数据、心率数据、血压数据、血糖数据、血氧数据、胆固醇数据和尿酸数据等。所述人体体征由采集设备进行采集，采集设备可以为便携式可穿戴设备或医院检测设备。
优选地，所述健康预警系统的数据库存储在云端服务器。
可选地，显示单元根据匹配度的大小进行排序显示。优选地，按照匹配度大小降序排序显示、根据疾病的危险程度进行显示或根据疾病的类型进行分类显示。
进一步地，所述人体体征数据库记录人体的历史体征数据记录，显示单元还输出所述预警疾病关联的异常指标的历史数据变化信息，优选地，以统计趋势图方式进行显示异常指标的历史数据变化趋势。
优选地，所述匹配度的计算公式为：
Figure PCTCN2020128908-appb-000001
其中i表示异常指标序号，j表示疾病序号；P j表示疾病j的风险匹配度；
Figure PCTCN2020128908-appb-000002
表示某种疾病j的各异常指标的权重系数；factor i表示异常指标i的指标值，f s表示参考值，f sL表示参考值下限，f sH表示参考值上限。可选地，f s取f sL和f sH的中值，即f s＝(f sL+f sH)/2。
进一步地，所述数据库系统还包括疾病关联数据库；预警单元与所述疾病关联数据库连接，当预警单元对某一种或多种疾病发出预警时，预警单元还调用疾病关联数据库，并根据疾病关联数据库，输出疾病的关联信息。所述疾病的关联信息包括但不限于疾病的发病年龄、病灶特征、疾病预防、疾病诊治知识、疾病的注意事项(例如饮食)、就医指导等信息。
进一步地，所述数据库系统还包括个人病历数据库和家族遗传病信息数据库。所述个人病历数据库用于记录个人的基本身份信息和历史就诊信息，所述家族遗传病信息数据库用于记录个人的家族遗传病信息；所述家族遗传病信息数据库与所述疾病与异常体征关联数据库和所述疾病关联数据库关联，得到家族遗传病的异常体征指标信息和疾病的关联信息，根据疾病关联信息中的发病年龄、病灶特征等信息，与个人病历数据库中的个人年龄、历史诊断记录信息关联以判断家族遗传病的风险，并将所述判断结果输出到所述预警单元。
进一步地，所述健康预警系统还包括预警效果反馈单元和自适应调节单元，所述自适应调节单元根据所述预警效果的反馈单元的统计信息，自适应反馈调整匹配度，从而提高预警的可信度。
进一步地，还包括个体疾病检查数据库，用于记录个人为进一步确认疾病所进行的相关检查、影像，以及医生或人工智能系统所得到的结论等。其中，所述预警效果反馈单元与所述个体疾病检查数据库相连，用于获取预警疾病后续检查得到的结论。
第二方面，本发明提供一种健康预警方法，包括：
将采集设备采集到的人体体征数据发送给云服务器端的人体体征数据库；
比较人体体征数据与正常指标范围的差异，并输出异常指标信息；
根据异常指标信息在疾病与异常体征关联数据库中匹配可能的疾病，并根据异常指标信息与疾病关联异常指标的匹配情况计算匹配度；
对于匹配度超过设定阈值的疾病进行预警。
优选地，所述匹配度计算公式为:
Figure PCTCN2020128908-appb-000003
其中
Figure PCTCN2020128908-appb-000004
或f s＝(f sL+f sH)/2，其中i表示异常指标序号，j表示疾病序号；P j表示疾病j的风险匹配度；
Figure PCTCN2020128908-appb-000005
表示某种疾病j的各异常指标的权重系数；factor i表示异常指标i的指标值，f s表示参考值，f sL表示参考值下限，f sH表示参考值上限；
还包括家族遗传病风险预警的步骤，数据库系统还包括个人病历数据库和家族遗传病信息数据库，所述个人病历数据库用于记录个人的基本身份信息和历史就诊信息，所述家族遗传病信息数据库用于记录个人的家族遗传病信息，所述家族遗传病信息数据库与所述疾病与异常体征关联数据库和所述疾病关联数据库关联，得到家族遗传病的异常体征指标信息和疾病的关联信息，至少根据疾病关联信息中的发病年龄和/或病灶特征信息，与个人病历数据库中的个人年龄、历史诊断记录信息关联以判断家族遗传病的风险，并将所述判断结果输出到所述预警单元；
对某一种或多种疾病发出预警时，预警单元还调用疾病关联数据库，并根据疾病关联数据库，输出疾病的关联信息；所述疾病的关联信息包括但不限于疾病的发病年龄、病灶特征、疾病预防、疾病诊治知识、疾病的注意事项、就医指导。
还包括显示步骤，用于显示疾病与匹配度信息以及预警信息，所述显示步骤在终端设备上进行，而所述匹配和预警可以在云端完成；显示单元按照匹配度大小降序排序显示、根据疾病的危险程度进行显示或根据疾病的类型进行分类显示；显示步骤还显示预警疾病关联的异常指标的历史数据变化信息，以统计趋势图方式进行显示异常指标的历史数据变化趋势。
还包括预警效果反馈与自适应调整步骤，预警效果反馈单元与个体疾病检查数据库相连，用于获取预警疾病后续检查得到的结论，自适应调节单元根据预警效果反馈单元的统计信息，自适应反馈调整匹配度，从而提高预警的可信度。
综上所述，本发明具有以下有益效果：能够根据个人的体征数据的异常数据的监控，并与疾病的体征数据的异常相互关联，并根据指标出现的数量和异常值计算匹配度，并根据匹配度来进行疾病的风险预警，同时，本发明还可以对家族遗传疾病进行监控，最大限度的预警家族病的出现风险，做到早诊早疗，在预测疾病危险和个性化健康管理及指导方面具有重要的意义。
附图说明
图1是实施例中的一种健康预警系统的示意图
图2是实施例中的另一种健康预警系统的示意图
图3是实施例中的健康预警系统的终端预警显示信息示意图
图4是实施例中健康预警方法的流程示意图
具体实施方式
以下结合附图对本发明作进一步详细说明。
如图1所示，一种健康预警系统，包括：数据库系统，所述数据库系统至少包括人体体征数据库、疾 病与异常体征关联数据库；比较单元，用于比较人体体征数据与正常指标范围的差异，并输出异常指标信息；匹配单元，根据比较单元输出的异常体征指标信息在所述疾病与异常体征关联数据库中匹配可能的疾病，并根据异常指标信息与疾病关联异常指标的匹配情况计算匹配度；预警单元，根据匹配度信息，对于匹配度超过设定阈值的疾病进行预警；显示单元，用于显示匹配单元输出的疾病与匹配度信息以及预警信息；
其中，比较单元与人体体征数据库相连；匹配单元分别与所述比较单元和所述疾病关联数据库连接；预警单元与所述比较单元或所述匹配单元连接；显示单元与所述预警单元连接。
所述人体体征包括但不限于脉波数据、体温数据、心率数据、血压数据、血糖数据、血氧数据、胆固醇数据和尿酸数据等。所述人体体征由采集设备进行采集，采集设备可以为便携式可穿戴设备或医院检测设备。
优选地，所述健康预警系统的数据库存储在云端服务器。
可选地，显示单元根据匹配度的大小进行排序显示。优选地，按照匹配度大小降序排序显示、根据疾病的危险程度进行显示或根据疾病的类型进行分类显示。
进一步地，所述人体体征数据库记录人体的历史体征数据记录，显示单元还输出所述预警疾病关联的异常指标的历史数据变化信息，优选地，以统计趋势图方式进行显示异常指标的历史数据变化趋势。
优选地，所述匹配度的计算公式为：
Figure PCTCN2020128908-appb-000006
其中i表示异常指标序号，j表示疾病序号；P j表示疾病j的风险匹配度；
Figure PCTCN2020128908-appb-000007
表示某种疾病j的各异常指标的权重系数；factor i表示异常指标i的指标值，f s表示参考值，f sL表示参考值下限，f sH表示参考值上限。可选地，f s取f sL和f sH的中值。
作为本发明的另一实施例，如图2所示，一种健康预警系统，包括：数据库系统，所述数据库系统至少包括人体体征数据库、疾病与异常体征关联数据库、个人病历数据库和家族遗传病信息数据库、疾病关联数据库；比较单元，用于比较人体体征数据与正常指标范围的差异，并输出异常指标信息；匹配单元，根据比较单元输出的异常体征指标信息在所述疾病与异常体征关联数据库中匹配可能的疾病，并根据异常指标信息与疾病关联异常指标的匹配情况计算匹配度；预警单元，根据匹配度信息，对于匹配度超过设定阈值的疾病进行预警；显示单元，用于显示匹配单元输出的疾病与匹配度信息以及预警信息；
其中，比较单元与人体体征数据库相连；匹配单元分别与所述比较单元和所述疾病关联数据库连接；预警单元与所述比较单元或所述匹配单元连接；显示单元与所述预警单元连接；预警单元与所述疾病关联数据库连接，当预警单元对某一种或多种疾病发出预警时，预警单元还调用疾病关联数据库，并根据疾病关联数据库，输出疾病的关联信息；所述疾病的关联信息包括但不限于疾病的发病年龄、病灶特征、疾病预防、疾病诊治知识、疾病的注意事项(例如饮食)、就医指导等信息；
所述家族遗传病信息数据库与所述疾病与异常体征关联数据库和所述疾病关联数据库关联，得到家族遗传病的异常体征指标信息和疾病的关联信息，根据疾病关联信息中的发病年龄、病灶特征等信息，与个人病历数据库中的个人年龄、历史诊断记录信息关联以判断家族遗传病的风险，并将所述判断结果输出到 所述预警单元；
所述个人病历数据库用于记录个人的基本身份信息和历史就诊信息，所述家族遗传病信息数据库用于记录个人的家族遗传病信息。
可选地，疾病关联数据库提供疾病相关信息的功能模块与由个人病历数据库、家族病数据库和疾病与异常体征关联数据库形成的针对家族病的预警功能模块可以单独存在，并根据需要在系统中进行配置。
进一步地，所述健康预警系统还包括预警效果反馈单元和自适应调节单元，所述自适应调节单元根据所述预警效果的反馈单元的统计信息，自适应反馈调整匹配度，从而提高预警的可信度。
进一步地，还包括个体疾病检查数据库，用于记录个人为进一步确认疾病所进行的相关检查、影像，包括医生或人工智能系统所得到的结论等。其中，所述预警效果反馈单元与所述个体疾病检查数据库相连，用于获取预警疾病后续检查得到的结论。
作为本发明的另一实施例，如图3所示，其为移动终端上的显示单元所展示的个人健康风险预警系统的示例。由图可见，该显示单元可以显示个人的姓名、编号；此外该显示单元还对匹配度超过某设定阈值的疾病进行显示。优选地，不同疾病类型设置不同的阈值。同时，根据匹配度对疾病进行排序，并对不同风险水平的疾病以不同的颜色进行显示，如图中不同颜色的小三角形。此外，显示单元还可以对各种异常指标进行显示，同时可以查询某项异常指标的历史变化趋势图。在显示单元的下方，设有疾病知识、疾病预防、饮食健康、体检资料、就医指导、疾病诊治等模块，可以根据需要点击进入相关模块进行查看。此外，系统还具有一键出报告功能，将风险预警信息以报告方式进行展示。优选地，所述输出方式可以为PDF格式。
作为本发明的另一实施例，如图4所示。一种健康预警方法，包括：
步骤S1，将采集设备采集到的人体体征数据发送给云服务器端的人体体征数据库；
步骤S2，比较人体体征数据与正常指标范围的差异，并输出异常指标信息；
步骤S3，根据异常指标信息在疾病与异常体征关联数据库中匹配可能的疾病，并根据异常指标信息与疾病关联异常指标的匹配情况计算匹配度；
步骤S4，对于匹配度超过设定阈值的疾病进行预警。
优选地，所述匹配度的计算公式为：
Figure PCTCN2020128908-appb-000008
其中i表示异常指标序号，j表示疾病序号；P j表示疾病j的风险匹配度；
Figure PCTCN2020128908-appb-000009
表示某种疾病j的各异常指标的权重系数；factor i表示异常指标i的指标值，f s表示参考值，f sL表示参考值下限，f sH表示参考值上限。可选地，f s取f sL和f sH的中值。
进一步地，作为另一实施例，本发明的方法还包括显示步骤，用于显示疾病与匹配度信息以及预警信息。可选地，所述显示步骤在终端设备上进行，而所述匹配和预警可以在云端完成。
所述人体体征由采集设备进行采集，采集设备可以是便携式可穿戴设备或医院检测设备。上述健康预警方法，在将采集设备采集到的人体体征数据发送给云服务器端之前，还包括：判断所述采集设备采集到的人体体征数据是否有效；若所述人体体征数据有效，则执行将所述人体体征数据发送给所述云服务器端 的步骤，其中，所述人体体征包括但不限于脉波数据、体温数据、心率数据、血压数据、血糖数据、血氧数据、胆固醇数据和尿酸数据等。
进一步地，对某一种或多种疾病发出预警时，预警单元还调用疾病关联数据库，并根据疾病关联数据库，输出疾病的关联信息。所述疾病的关联信息包括疾病的发病年龄、病灶特征、疾病预防、疾病诊治知识、疾病的注意事项(例如饮食)、就医指导等信息。
可选地，显示单元根据匹配度的大小进行排序显示。优选地，按照匹配度大小降序排序显示、根据疾病的危险程度进行显示或根据疾病的类型进行分类显示。
进一步地，所述人体体征数据库记录人体的历史体征数据记录，显示步骤还显示预警疾病关联的异常指标的历史数据变化信息，优选地，以统计趋势图方式进行显示异常指标的历史数据变化趋势。
进一步地，作为本发明的另一实施例，还包括疾病关联信息获取和显示步骤，预警单元与疾病关联数据库连接，当预警单元对某一种或多种疾病发出预警时，预警单元还调用疾病关联数据库，并根据疾病关联数据库，输出疾病的关联信息。所述疾病的关联信息包括但不限于疾病的发病年龄、病灶特征、疾病预防、疾病诊治知识、疾病的注意事项(例如饮食)、就医指导等信息。
进一步地，作为本发明的另一实施例，还包括家族遗传病风险预警的步骤。数据库系统还包括个人病历数据库和家族遗传病信息数据库，所述个人病历数据库用于记录个人的基本身份信息和历史就诊信息，所述家族遗传病信息数据库用于记录个人的家族遗传病信息。所述家族遗传病信息数据库与所述疾病与异常体征关联数据库和所述疾病关联数据库关联，得到家族遗传病的异常体征指标信息和疾病的关联信息，根据疾病关联信息中的发病年龄、病灶特征等信息，与个人病历数据库中的个人年龄、历史诊断记录信息关联以判断家族遗传病的风险，并将所述判断结果输出到所述预警单元。
进一步地，作为本发明的另一实施例，还包括预警效果反馈与自适应调整步骤，自适应调节单元根据预警效果反馈单元的统计信息，自适应反馈调整匹配度，从而提高预警的可信度。
进一步地，作为本发明的另一实施例，还包括个体疾病检查数据库，用于记录个人为进一步确认疾病所进行的相关检查、影像，包括医生或人工智能系统所得到的结论等。其中，所述预警效果反馈单元与所述个体疾病检查数据库相连，用于获取预警疾病后续检查得到的结论。
本具体实施例仅仅是对本发明的解释，其并不是对本发明的限制，本领域技术人员在阅读完本说明书后可以根据需要对本实施例做出没有创造性贡献的修改，但只要在本发明的权利要求范围内都受到专利法的保护。

Claims (10)

  1. 一种健康预警系统，包括：数据库系统，所述数据库系统至少包括人体体征数据库、疾病与异常体征关联数据库；比较单元，用于比较人体体征数据与正常指标范围的差异，并输出异常指标信息；匹配单元，根据比较单元输出的异常体征指标信息在所述疾病与异常体征关联数据库中匹配可能的疾病，并根据异常指标信息与疾病关联异常指标的匹配情况计算匹配度；预警单元，根据匹配度信息，对于匹配度超过设定阈值的疾病进行预警；显示单元，用于显示匹配单元输出的疾病与匹配度信息以及预警信息；
    其中，比较单元与人体体征数据库相连；匹配单元分别与所述比较单元和所述疾病关联数据库连接；预警单元与所述比较单元或所述匹配单元连接；显示单元与所述预警单元连接。
  2. 根据权利要求1所述的健康预警系统，其特征在于：所述数据库系统还包括疾病关联数据库，预警单元与所述疾病关联数据库连接，当预警单元对某一种或多种疾病发出预警时，预警单元还调用疾病关联数据库，并根据疾病关联数据库，输出疾病的关联信息；所述疾病的关联信息包括但不限于疾病的发病年龄、病灶特征、疾病预防、疾病诊治知识、疾病的注意事项、就医指导信息。
  3. 根据权利要求2所述的健康预警系统，其特征在于：所述数据库系统还包括个人病历数据库和家族遗传病信息数据库，所述个人病历数据库用于记录个人的基本身份信息和历史就诊信息，所述家族遗传病信息数据库用于记录个人的家族遗传病信息；所述家族遗传病信息数据库与所述疾病与异常体征关联数据库和所述疾病关联数据库关联，得到家族遗传病的异常体征指标信息和疾病的关联信息，至少根据疾病关联信息中的发病年龄和/或病灶特征信息，与个人病历数据库中的个人年龄、历史诊断记录信息关联以判断家族遗传病的风险，并将判断结果输出到所述预警单元。
  4. 根据权利要求3所述的健康预警系统，其特征在于，匹配度的计算公式为：
    Figure PCTCN2020128908-appb-100001
    其中
    Figure PCTCN2020128908-appb-100002
    或f s＝(f sL+f sH)/2，其中i表示异常指标序号，j表示疾病序号；P j表示疾病j的风险匹配度；
    Figure PCTCN2020128908-appb-100003
    表示某种疾病j的各异常指标的权重系数；factor i表示异常指标i的指标值，f s表示参考值，f sL表示参考值下限，f sH表示参考值上限。
  5. 根据权利要求4所述的健康预警系统，其特征在于：还包括个体疾病检查数据库，用于记录个人为进一步确认疾病所进行的相关检查、影像，以及医生或人工智能系统所得到的结论；还包括预警效果反馈单元和自适应调节单元，所述自适应调节单元根据所述预警效果的反馈单元的统计信息，自适应反馈调整匹配度，从而提高预警的可信度；其中，所述预警效果反馈单元与所述个体疾病检查数据库相连，用于获取预警疾病后续检查得到的结论。
  6. 根据权利要求5所述的健康预警系统，其特征在于：显示单元按照匹配度大小降序排序显示、根据疾病的危险程度进行显示或根据疾病的类型进行分类显示；显示单元还显示预警疾病关联的异常指标的历史数据变化信息，以统计趋势图方式进行显示异常指标的历史数据变化趋势。
  7. 一种健康预警方法，包括：
    将采集设备采集到的人体体征数据发送给云服务器端的人体体征数据库；
    比较人体体征数据与正常指标范围的差异，并输出异常指标信息；
    根据异常指标信息在疾病与异常体征关联数据库中匹配可能的疾病，并根据异常指标信息与疾病关联 异常指标的匹配情况计算匹配度；
    对于匹配度超过设定阈值的疾病进行预警。
  8. 根据权利要求7所述的健康预警方法，其特征在于：
    所述匹配度计算公式为
    Figure PCTCN2020128908-appb-100004
    其中
    Figure PCTCN2020128908-appb-100005
    或f s＝(f sL+f sH)/2，其中i表示异常指标序号，j表示疾病序号；P j表示疾病j的风险匹配度；
    Figure PCTCN2020128908-appb-100006
    表示某种疾病j的各异常指标的权重系数；factor i表示异常指标i的指标值，f s表示参考值，f sL表示参考值下限，f sH表示参考值上限；
    还包括家族遗传病风险预警的步骤，数据库系统还包括个人病历数据库和家族遗传病信息数据库，所述个人病历数据库用于记录个人的基本身份信息和历史就诊信息，所述家族遗传病信息数据库用于记录个人的家族遗传病信息，所述家族遗传病信息数据库与所述疾病与异常体征关联数据库和所述疾病关联数据库关联，得到家族遗传病的异常体征指标信息和疾病的关联信息，至少根据疾病关联信息中的发病年龄和/或病灶特征信息，与个人病历数据库中的个人年龄、历史诊断记录信息关联以判断家族遗传病的风险，并将所述判断结果输出到所述预警单元；
    对某一种或多种疾病发出预警时，预警单元还调用疾病关联数据库，并根据疾病关联数据库，输出疾病的关联信息；所述疾病的关联信息包括但不限于疾病的发病年龄、病灶特征、疾病预防、疾病诊治知识、疾病的注意事项、就医指导。
  9. 根据权利要求8所述的健康预警方法，其特征在于：
    还包括显示步骤，用于显示疾病与匹配度信息以及预警信息，所述显示步骤在终端设备上进行，而所述匹配和预警可以在云端完成；显示单元按照匹配度大小降序排序显示、根据疾病的危险程度进行显示或根据疾病的类型进行分类显示；显示步骤还显示预警疾病关联的异常指标的历史数据变化信息，以统计趋势图方式进行显示异常指标的历史数据变化趋势。
  10. 根据权利要求9所述的健康预警方法，其特征在于：
    还包括预警效果反馈与自适应调整步骤，预警效果反馈单元与个体疾病检查数据库相连，用于获取预警疾病后续检查得到的结论，自适应调节单元根据预警效果反馈单元的统计信息，自适应反馈调整匹配度，从而提高预警的可信度。
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