CN111048201A - Intelligent cancer risk prediction method and system - Google Patents
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Abstract
The invention discloses an intelligent cancer risk prediction method and system. The user starts answering the question by touching the screen "start" button at the touchable interactive interface; the artificial intelligent voice system can directly interact with the user, read each question that the user needs to answer, and give answers meeting the self condition according to the heard questions; the internal memory of the terminal is preset with the alternative answers of each question, possible risk factors corresponding to each cancer and the relative risk of each risk factor and the corresponding cancer; the system can enable the user to predict the cancer risk in various scenes, provides a simple and easy cancer risk screening means for the user, and can better prevent public cancer risk.
Description
Technical Field
The invention relates to the technical field of health management, in particular to an intelligent cancer risk prediction method and system.
Background
Cancer or malignant tumor is a general term for more than 100 related diseases. Cancer is a serious public health problem worldwide, with approximately 800 million people dying from cancer worldwide each year. In China, more than 400 million new cancer cases occur each year, accounting for 20% of new cases worldwide, and more than 280 million death cases occur. The cancer seriously threatening the health of the masses is mainly lung cancer, besides the cancers with the highest mortality and morbidity in men, liver cancer, stomach cancer and esophagus cancer are also the cancers with the highest mortality and morbidity in women, breast cancer, stomach cancer and liver cancer are also the cancers. The incidence rate of cancer in China is close to the average level in the world, but the mortality rate is higher than the average level in the world and is further higher than the level of developed countries, wherein one important reason is that the early screening consciousness of the Chinese masses is weak, and the tumors are mostly in the middle and late stages when being discovered, so that the optimal treatment time is lost.
The occurrence of tumors, particularly malignant tumors, is mainly the result of the dual actions of congenital genetic factors and acquired environmental factors. About 10% of tumors in humans are inherited, and genetic variations in such tumors can be transmitted to offspring through reproduction, and although such tumors represent a small percentage of the total tumor burden, they are highly detrimental to individuals and families carrying such genetic variations. For example, genes inherited from BRCA1, can cause the incidence rate of breast cancer and ovarian cancer of individuals to be as high as 50% -80%. For example, hereditary nonpolyposis colorectal cancer (HNPCC) is caused by mutation of a susceptible gene, namely mismatch repair gene (MLH1, MSH2 and the like), and the risk of colorectal cancer in the life of a mutation carrier is 80 percent, while the risk of colorectal cancer in people without mutation is only about 2 percent. In addition, acquired environmental factors including innate factors, lifestyle and disease medication related cancer risk factors also have a significant impact on the development of malignant tumors.
90% of malignant tumors have no obvious symptoms in the early stage, and are usually found in the middle and late stages, so early detection, early prevention and early treatment are important means for preventing cancer. Health guidance under risk assessment is an important tool for researching and improving national physique and preventing and treating diseases at home and abroad in recent years, and has important significance in especially predicting disease risk and providing personalized health management and guidance. However, at present, no mature cancer prevention health management system exists in China, and people in China have little knowledge of the benefits of the cancer prevention health management system, but health risk assessment is popularized and accepted in the future. Cancer prevention generally requires experts to know about individual health conditions, but the expert resources are relatively limited, and the requirements of various scenes of the general public cannot be met, in addition, an international cancer risk prediction system mainly models, evaluates and predicts the characteristics of western people, and the acquired risk factors of the Chinese population are obviously different from those of the western people, so that no cancer prevention system suitable for Chinese exists.
Disclosure of Invention
The invention aims to provide a simple and easy cancer risk prediction method which is applicable to various scenes and is provided for users, and the method mainly comprises the following steps:
s1, collecting personal acquired environmental factor data of cancer, interacting with a user through an intelligent interaction terminal with a touch screen interaction interface and an artificial intelligent voice system, starting questionnaire investigation by the user on the touch screen interaction interface, transmitting the text questions to the user through the artificial intelligent voice system by converting the text questions into voice, answering the voice by the user after hearing the voice, and jumping to the next question after recognizing the voice information of the user by the artificial intelligent voice system;
s2, comparing and analyzing the user answer and the system alternative answer, wherein after the intelligent interactive terminal obtains the user answer voice information, the system processor identifies the matching degree of the user answer and the alternative answer, and determines and records the answer of each question;
s3, calculating the risk of the cancer, generating risk factors corresponding to the cancer by the system processor of the intelligent interactive terminal according to the recorded answers after the user finishes all questionnaires, and predicting the risk of the cancer by using a cancer risk evaluation model;
and S4, generating a personalized cancer prevention scheme report, wherein the system processor generates the personalized cancer prevention scheme report and returns the report to the interactive interface for the user to view after completing the occurrence risk of each cancer.
In step S1, after the interactive intelligent device finishes reading a question, it waits for the user to respond, where the waiting time is 1 minute, and after the artificial intelligent speech system receives the speech answered by the user within 1 minute, it jumps to the next question; if the artificial intelligent voice system does not receive external voice feedback within 1 minute, the touch screen interactive interface prompts the user whether to continue answering, and if the user still does not answer or the user answers 'no', the user automatically jumps to the initial interface; if the answer is 'yes', the intelligent interactive terminal continues to wait for the voice feedback of the user.
In the personalized cancer prevention scheme report generated in step S4, high, medium and low grades are performed according to the calculated relative risk value of individual cancer, and the grades are visually displayed in the system by using three colors of red, yellow and green.
The intelligent interaction terminal comprises an intelligent robot, an intelligent mobile phone, a wearable intelligent terminal and an intelligent television.
Another aspect of the present invention provides a system for implementing the above intelligent cancer risk prediction method, including an intelligent interactive terminal, where the intelligent interactive terminal has a touch-screen operation interface, an artificial intelligence voice system, an internal memory, and a system processor, where the touch-screen operation interface has a question display component and an operation button component; the artificial intelligence voice system converts the displayed problem into voice, simultaneously identifies the voice feedback of the user, and stores the identification result into the internal memory; the system processor identifies the matching degree of the user answers and the alternative answers, determines and records the answers of each question, generates risk factors corresponding to the cancers according to the recorded answers, predicts the risks of the cancers by using a cancer risk assessment model, and finally generates a personalized cancer prevention scheme report and returns the report to the interactive interface.
The cancer prediction method adopts intelligent interaction equipment, can be suitable for collecting acquired environmental factors of cancer of a user in various scenes, provides a simple and easy cancer risk screening means for the user, and can better prevent public cancer risk.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing embodiments thereof with reference to the accompanying drawings in which:
FIG. 1 shows a flow chart of a cancer risk prediction method of the present invention;
FIG. 2 shows a functional schematic of the cancer risk prediction system of the present invention;
Detailed Description
Embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples.
As shown in fig. 1, an embodiment of the present invention provides an intelligent cancer risk prediction method, which mainly includes the following steps:
firstly, step S1 is performed to collect environmental factor data of an individual after cancer: the method comprises the steps that interaction is carried out between the intelligent interaction terminal with the touch screen interactive interface and the artificial intelligent voice system, a user starts questionnaire investigation on the touch screen interactive interface, the artificial intelligent voice system converts character questions into voice and transmits the voice to the user, the user answers the voice after hearing the voice, and the artificial intelligent voice system recognizes voice information of the user and then jumps to the next question.
After the intelligent interactive terminal finishes reading a question, waiting for the response of the user, wherein the waiting time is 1 minute, and after the artificial intelligent voice system receives the voice answered by the user within 1 minute, skipping to the next question; if the artificial intelligent voice system does not receive external voice feedback within 1 minute, the touch screen interactive interface prompts the user whether to continue answering, and if the user still does not answer or the user answers 'no', the user automatically jumps to the initial interface; if the answer is yes, the interactive device continues to wait for user voice feedback.
Wherein, having stored preset problem among the intelligent interaction terminal, having covered the risk factor of 30 kinds of cancers that can calculate, including congenital factor, life style and disease medication relevant cancer risk factor, congenital factor includes: sex, age, height, weight, family history, fertility status, etc.; the life style comprises the following steps: smoking, drinking, exercise, sedentary time, etc.; the disease medication comprises: hepatitis B or hepatitis C virus infection, diabetes, gallstone, cholecystectomy, metformin, and the like.
Then, step S2 is performed to compare and analyze the user answer and the system candidate answer. After the intelligent interactive terminal obtains the user answer voice information, the system processor of the intelligent interactive terminal can identify the matching degree of the user answers and the alternative answers, and determine and record the answers of each question. After the user completes all questionnaires, step S3 is performed to calculate the individual cancer risk, the system processor of the intelligent interactive terminal generates the risk factor corresponding to the cancer according to the recorded answers, and the cancer risk assessment model is used to predict the cancer risk.
And aiming at the collected personal cancer risk factor data, looking up documents to obtain the relative risk of the cancer risk factors, searching data to obtain the incidence of the risk factors, and estimating the incidence of the personal cancer by calculation of a Harvard model. The Harvard cancer risk prediction model is developed by a risk index working group of the Harvard cancer prevention center, and is a calculation model for simply and directly predicting the risk of a certain cancer. However, the model is more suitable for western people, so when the cancer risk prediction of Chinese people is carried out, the model is locally improved. When determining the included cancer risk factors, by determining a rating table of the applicability of the risk factors in the Chinese population, evaluating and screening the retrieved risk factor documents of each cancer by using the rating table, the risk factors and OR/RR values which are more suitable for the Chinese population are included, wherein RR (relative risk) means that the morbidity OR mortality of an exposure group is more than that of a control group, OR (odds ratio) means that the disease risk of the exposure group is more than that of a non-exposure group, the incidence of the cancer is very low compared with other common chronic diseases (such as diabetes, hypertension and the like) and the outcome is difficult to track, and the relationship between the risk factors and the cancer can be judged according to the ratio of OR/RR, and generally has the following relationship:
OR/RR >1, suggesting that risk factors may increase the incidence of cancer
OR/RR ═ 1, indicates that risk factors are not statistically correlated with carcinogenesis
OR/RR <1, indicates that risk factors may reduce the incidence of cancer.
When the model is really calculated, a certain weight value is given to each risk factor, so that the proportion of each risk factor can be adjusted in time after the numerical value of the real population is used in the later period. And finally, calculating the relative risk value of the individual suffering from the cancer aiming at the individual cancer risk factor indexes according to the relative risk and incidence of different cancer risk factors and the weight of each cancer risk factor.
And calculating the relative risk value of the individual suffering from the cancer, namely the multiple of the average risk of suffering from the cancer of the people of the same age. The cancer risk is divided into three grades of high, slightly high and low according to the fold. A "factor > 2.0" indicates that the risk of cancer for the user is at least 2 times greater than the average risk, suggesting that the risk of cancer is higher, "1.0 < factor ≦ 2.0" indicates that the risk of cancer is slightly higher, and "factor ≦ 1.0" indicates that the risk of cancer is close to or lower than the average population. The intelligent interactive terminal calculates the relative risk value of the individual cancer according to the collected individual cancer risk factors of the user, generates an individual cancer prevention scheme report of the user according to the step S4, transmits the report to an interactive interface of the intelligent interactive terminal, carries out high, middle and low grading according to the calculated relative risk value of the individual cancer, and carries out visual display by adopting three colors of red, yellow and green in the system aiming at each grading.
FIG. 2 is a functional schematic diagram of an intelligent interactive terminal, including an intelligent interactive terminal, having a touch-screen operable interface with a question display component and an operation button component, an artificial intelligence voice system, an internal memory, and a system processor; the artificial intelligence voice system converts the displayed problem into voice, simultaneously identifies the voice feedback of the user, and stores the identification result into the internal memory; the system processor identifies the matching degree of the user answers and the alternative answers, determines and records the answers of each question, generates risk factors corresponding to the cancers according to the recorded answers, predicts the risks of the cancers by using a cancer risk assessment model, and finally generates a personalized cancer prevention scheme report and returns the report to the interactive interface.
The intelligent interactive terminal can be an intelligent robot, an intelligent mobile phone, a wearable intelligent terminal and an intelligent television and is applied to different scenes. For example, the intelligent interactive terminal can be placed in medical and health places or disease prevention related places such as community hospitals, hospitals at all levels, physical examination centers and the like, and users answer questions and provide individual saliva samples to perform individual cancer risk prediction to obtain personalized health management schemes. In addition, the intelligent terminal can also be applied to families, and data acquisition of personal living habits can be carried out through the smart television, the smart phone or wearable equipment.
Although the invention has been described in detail hereinabove with respect to specific embodiments thereof, it will be apparent to those skilled in the art that modifications and improvements can be made thereto without departing from the scope of the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.
Claims (5)
1. An intelligent cancer risk prediction method, comprising the steps of:
s1, collecting personal acquired environmental factor data of cancer, interacting with a user through an intelligent interaction terminal with a touch screen interaction interface and an artificial intelligent voice system, starting questionnaire investigation by the user on the touch screen interaction interface, transmitting the text questions to the user through the artificial intelligent voice system by converting the text questions into voice, answering the voice by the user after hearing the voice, and jumping to the next question after recognizing the voice information of the user by the artificial intelligent voice system;
s2, comparing and analyzing the user answer and the system alternative answer, wherein after the intelligent interactive terminal obtains the user answer voice information, the system processor identifies the matching degree of the user answer and the alternative answer, and determines and records the answer of each question;
s3, calculating the risk of the cancer, generating risk factors corresponding to the cancer by the system processor of the intelligent interactive terminal according to the recorded answers after the user finishes all questionnaires, and predicting the risk of the cancer by using a cancer risk evaluation model;
and S4, generating a personalized cancer prevention scheme report, wherein the system processor generates the personalized cancer prevention scheme report and returns the report to the interactive interface for the user to view after completing the occurrence risk of each cancer.
2. The intelligent cancer risk prediction method of claim 1, wherein in step S1, after the interactive intelligent device finishes reading a question, the interactive intelligent device waits for a response from the user, the waiting time is 1 minute, and after the artificial intelligent voice system receives the voice of the user response within 1 minute, the next question is skipped; if the artificial intelligent voice system does not receive external voice feedback within 1 minute, the touch screen interactive interface prompts the user whether to continue answering, and if the user still does not answer or the user answers 'no', the user automatically jumps to the initial interface; if the answer is 'yes', the intelligent interactive terminal continues to wait for the voice feedback of the user.
3. The intelligent cancer risk prediction method of claim 1, wherein the personalized cancer prevention program report generated in step S4 is classified into high, medium and low levels according to the calculated relative risk value of individual cancer, and the system is visually displayed with red, yellow and green colors for each of the classifications.
4. The intelligent cancer risk prediction method of claim 1 wherein the intelligent interactive terminal comprises a smart robot, a smart phone, a wearable smart terminal, a smart television.
5. A system for implementing the intelligent cancer risk prediction method according to claims 1-4, comprising an intelligent interactive terminal, wherein the intelligent interactive terminal has a touch-screen operation interface, an artificial intelligence voice system, an internal memory, and a system processor, wherein the touch-screen operation interface has a question display component and an operation button component; the artificial intelligence voice system converts the displayed problem into voice, simultaneously identifies the voice feedback of the user, and stores the identification result into the internal memory; the system processor identifies the matching degree of the user answers and the alternative answers, determines and records the answers of each question, generates risk factors corresponding to the cancers according to the recorded answers, predicts the risks of the cancers by using a cancer risk assessment model, and finally generates a personalized cancer prevention scheme report and returns the report to the interactive interface.
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113808741A (en) * | 2021-10-08 | 2021-12-17 | 国家癌症中心 | Cancer prevention and control intelligent network platform |
CN114121263A (en) * | 2021-11-08 | 2022-03-01 | 绵阳富临医院有限公司 | Artificial intelligence auxiliary early gastric cancer and lung cancer screening system |
JP2023021479A (en) * | 2021-08-02 | 2023-02-14 | 浩司 吉田 | Pancreatic cancer diagnosis system |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20050273359A1 (en) * | 2004-06-03 | 2005-12-08 | Young David E | System and method of evaluating preoperative medical care and determining recommended tests based on patient health history and medical condition and nature of surgical procedure |
CN108847283A (en) * | 2018-04-19 | 2018-11-20 | 中国人民解放军第二军医大学 | Personalized health management method and system |
US20190172571A1 (en) * | 2017-12-01 | 2019-06-06 | Elements of Genius, Inc. | Enhanced assistive mobility devices |
CN110211704A (en) * | 2019-05-05 | 2019-09-06 | 平安科技(深圳)有限公司 | The engine method and server of matter of opening |
-
2019
- 2019-12-02 CN CN201911214937.8A patent/CN111048201A/en active Pending
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20050273359A1 (en) * | 2004-06-03 | 2005-12-08 | Young David E | System and method of evaluating preoperative medical care and determining recommended tests based on patient health history and medical condition and nature of surgical procedure |
US20190172571A1 (en) * | 2017-12-01 | 2019-06-06 | Elements of Genius, Inc. | Enhanced assistive mobility devices |
CN108847283A (en) * | 2018-04-19 | 2018-11-20 | 中国人民解放军第二军医大学 | Personalized health management method and system |
CN110211704A (en) * | 2019-05-05 | 2019-09-06 | 平安科技(深圳)有限公司 | The engine method and server of matter of opening |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2023021479A (en) * | 2021-08-02 | 2023-02-14 | 浩司 吉田 | Pancreatic cancer diagnosis system |
JP7324252B2 (en) | 2021-08-02 | 2023-08-09 | 浩司 吉田 | Pancreatic cancer diagnosis system |
CN113808741A (en) * | 2021-10-08 | 2021-12-17 | 国家癌症中心 | Cancer prevention and control intelligent network platform |
CN113808741B (en) * | 2021-10-08 | 2022-04-22 | 国家癌症中心 | Cancer prevention and control intelligent network platform |
CN114121263A (en) * | 2021-11-08 | 2022-03-01 | 绵阳富临医院有限公司 | Artificial intelligence auxiliary early gastric cancer and lung cancer screening system |
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Application publication date: 20200421 |