Clinical somatic symptom classification diagnosis system

Abstract

The invention provides a clinical somatic symptom classification diagnosis system, and relates to the field of medical diagnosis. The system is composed of a user side and a background cloud server side. The user side is used for inputting patient body symptom characteristic data and checking results; the background cloud server comprises a cloud storage platform, a big data computing platform and an intelligent analysis platform; a clinical somatic symptom classification diagnosis scale is stored in the cloud storage platform, the big data calculation platform is used for calculating somatic symptom characteristic data of a patient, and the intelligent analysis platform is used for analyzing a diagnosis result. All operations of the clinical somatic symptom classification diagnosis system can be completed through the mobile terminal device, and the system is simple, efficient and convenient. The data is centrally stored in a back-end cloud platform database, support is provided for future research and analysis, efficient utilization of data resources is achieved, and a foundation is laid for AI artificial intelligence to achieve intelligent diagnosis.

Description

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AI Technical Summary

Benefits of technology

This patented innovative solution involves combining different types of tools (cloud computation, massage machine learning), with an algorithm that helps identify certain conditions called problems associated with healthy individuals who may have their own personalized senses such as body weight measurement and heart rate measurements. It then applies advanced techniques like deep learning algorithms to analyze these sensor readings and generate insights about them. These inspections are done overnight while still being carried out manually, reducing costs and increasing accuracy compared to traditional methods. Additionally, it includes automatic scoring functions to help evaluate questions quickly and efficiently during evaluation sessions. Overall, this new method simplifies the process of identifying physiological indicators related to diseases and enables effective therapy recommendations.

Problems solved by technology

This patented technical problem addressed in the patents relates to improving the accuracy and efficiency of identifying physician-patients with specific neurological conditions (such as those associated with Parkinson’ s Disease). Current categorizing or diagnostic techniques have limitations such as time consumption, lack precision, complexity, poor usability, limited ability to compare multiple datasets from one group, and potential issues like overlapping symptoms due to factors like medication side effects.

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