Medical diagnosis artificial intelligence system, device and self learning method thereof

Abstract

The invention provides a medical diagnosis artificial intelligence system, a device and a self learning method thereof. The method comprises the steps of performing original data acquisition; obtaining classified data; introducing the classified data into a data index algorithm, performing data conversion for forming visual data; and continuously performing data index algorithm verification; constructing a user profile by means of the visual data; determining whether a matched medical model can be found according to the user profile, and performing risk reminding; constructing a new medical model according to the user sample characteristic through a machine learning algorithm; performing self construction of a new data index algorithm according to the new medical model; and replacing the original data index algorithm by the new data index algorithm. According to the medical diagnosis artificial intelligence system, the device and the self learning method, data of a patient can be acquired and processing in 24 hours without an effect to the normal life of the user. Furthermore a medical diagnosis artificial intelligence platform according to the invention can perform self learning,thereby realizing high diagnosis accuracy and larger diagnosable disease range.

Description

technical field [0001] The invention relates to an artificial intelligence platform and its operating method, in particular to a self-learning medical diagnosis artificial intelligence system, device and self-learning method. Background technique [0002] Most of the current online medical diagnosis platforms stay on the website where the doctor resides, and the patient communicates with the doctor through network communication technology, and describes his illness to the doctor so that the doctor can make a diagnosis. This method has the following disadvantages: (1) The doctor cannot actually contact the patient, let alone see, hear and ask. If the patient cannot describe the symptoms clearly, it is likely to mislead the doctor to make a wrong judgment; (2) Due to the extremely limited information obtained , even if the doctor on the online medical diagnosis platform makes a diagnosis, the patient still has to go to the hospital for an examination in person to make a final ...

AI Technical Summary

Problems solved by technology

This method has the following disadvantages: (1) The doctor cannot actually contact the patient, let alone see, hear and ask. If the patient cannot describe the symptoms clearly, it is likely to mislead the doctor to make a wrong judgment; (2) Due to the extremely limited information obtained , even if the doctor on the online medical diagnosis platform makes a diagnosis, the patient still has to go to the hospital for an examination in person to make a final diagnosis, which makes the online medical diagnosis platform actually useless and wastes time for both patients and doctors; (3) Doctors do not have any reference data when making a diagnosis, which is very easy to make a misjudgment, resulting in irreversible consequences; (4) Since doctors have to rest at night, the online medical diagnosis platform is in a state of paralysis at night and cannot provide round-the-clock services patient

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