System, method, and device for personal medical care, intelligent analysis, and diagnosis

Abstract

A system includes a server having self-learning artificial intelligence that accesses medical information and personal medical data over a communication network. The server performs operations, including retrieving the personal medical data and medical information related to the personal medical data, and converting the retrieved personal medical data to fuzzy personal medical data by using the self-learning artificial intelligence to determine a plurality of fuzzy attributes for the personal medical data. The operations also include analyzing the converted fuzzy personal medical data together with the retrieved medical information, and identifying at least one issue requiring follow-up by the patient or by at least one external authorized entity. The operations further include transmitting the issue, the related analyzed converted fuzzy personal medical data, and the medical information via the communication network to the at least one external authorized entity for follow-up analysis and treatment.

What is claimed is: 
     
         1 . A system, comprising:
 at least one source of medical information;   at least one source of personal medical data for at least one patient; and   at least one server, including one or more processors, having self-learning artificial intelligence (AI) that accesses the medical information and the personal medical data over a communication network, the server performing operations, including
 retrieving the personal medical data and medical information related to the personal medical data, 
 converting the retrieved personal medical data to fuzzy personal medical data by using the self-learning artificial intelligence to determine a plurality of fuzzy attributes for the personal medical data, where a fuzzy attribute includes determining one or more fuzzy ranges of personal medical data values that are associated with discrete values or discrete ranges of the retrieved personal medical data, 
 analyzing the converted fuzzy personal medical data together with the retrieved medical information; 
 identifying at least one issue requiring follow-up by the patient or by at least one external authorized entity; and, 
 transmitting the issue, the related analyzed converted fuzzy personal medical data, and the medical information via the communication network to the at least one external authorized entity for follow-up analysis and treatment. 
   
     
     
         2 . The system of  claim 1 ,
 wherein a fuzzy range represents a variable range of values that are determined by the server using the self-learning Artificial Intelligence to incorporate acquired expert human judgement interpreting the discrete values and the discrete ranges, and defining their relationships to each other.   
     
     
         3 . The system of  claim 1 ,
 wherein the operations further include determining a plurality of fuzzy categories for the plurality of fuzzy attributes, wherein the fuzzy categories each have one or more fuzzy ranges that may overlap one another.   
     
     
         4 . The system of  claim 3 ,
 wherein the operations further include constructing a plurality of fuzzy functions corresponding to the plurality of fuzzy categories, wherein the plurality of fuzzy functions are constructed based on the plurality of fuzzy attributes and medical guideline data.   
     
     
         5 . The system of  claim 4 ,
 wherein the operations further include determining membership values in the plurality of fuzzy categories for the plurality of fuzzy attributes based on the plurality of fuzzy functions, and building a plurality of fuzzy tables for each of the plurality of fuzzy attributes.   
     
     
         6 . The system of  claim 1 ,
 wherein the self-learning artificial intelligence includes an artificial intelligence diagnosis protocol, an artificial intelligence therapy protocol, and an artificial intelligence inference engine.   
     
     
         7 . The system of  claim 1 , further comprising:
 a client personal electronic medical device, including
 a processor; 
 a memory for storing the personal medical data and related information for the at least one patient; 
 a graphical user interface (GUI) adapted to access and display the personal medical data and the related information for the at least one patient; 
 a microphone; 
 a speaker, and 
 a communication interface for communicating with the server over the communication network. 
   
     
     
         8 . A method, comprising:
 retrieving, using a server having self-learning artificial intelligence (AI), personal medical data and medical information related to the personal medical data for at least one patient;   converting the retrieved personal medical data to fuzzy personal medical data by using the self-learning artificial intelligence to determine a plurality of fuzzy attributes for the personal medical data, where a fuzzy attribute includes determining one or more fuzzy ranges of personal medical data values that are associated with discrete values or discrete ranges of the retrieved personal medical data,   analyzing the converted fuzzy personal medical data together with medical information retrieved by the server over the communication network;   identifying at least one issue requiring follow-up by the patient or by at least one external authorized entity; and,   transmitting the issue, the related analyzed converted fuzzy personal medical data, and the medical information via the communication network to the at least one external authorized entity for follow-up analysis and treatment.   
     
     
         9 . The system of  claim 8 ,
 wherein a fuzzy range represents a variable range of values that are determined by the server using the self-learning artificial intelligence to incorporate acquired expert human judgement interpreting the discrete values and the discrete ranges, and defining their relationships to each other.   
     
     
         10 . The method of  claim 8 ,
 wherein the method further includes determining a plurality of fuzzy categories for the plurality of fuzzy attributes, wherein the fuzzy categories each have one or more fuzzy ranges that may overlap one another.   
     
     
         11 . The system of  claim 10 ,
 wherein the operations further include constructing a plurality of fuzzy functions corresponding to the plurality of fuzzy categories, wherein the plurality of fuzzy functions are constructed based on the plurality of fuzzy attributes and medical guideline data.   
     
     
         12 . The system of  claim 11 ,
 wherein the operations further include determining membership values in the plurality of fuzzy categories for the plurality of fuzzy attributes based on the plurality of fuzzy functions, and building a plurality of fuzzy tables for each of the plurality of fuzzy attributes.   
     
     
         13 . The method of  claim 8 ,
 wherein the self-learning artificial intelligence includes an artificial intelligence diagnosis protocol, an artificial intelligence therapy protocol, and an artificial intelligence inference engine.   
     
     
         14 . The method of  claim 8 , further comprising:
 providing a client personal electronic medical device for communicating with the server over the communication network, the client personal electronic medical device including
 a processor, 
 a memory for storing the personal medical data and related information for the at least one patient; 
 a graphical user interface (GUI) adapted to access and display the personal medical data and the related information for the at least one patient; 
 a microphone; 
 a speaker; and 
 a communication interface for communicating with the server over the communication network. 
   
     
     
         15 . A non-transitory storage medium storing at one or more computer programs, which when executed by a server having self-learning artificial intelligence (AI), executes operations, including:
 retrieving, using the server having the self-learning artificial intelligence (AI), personal medical data and medical information related to the personal medical data for at least one patient;   converting the retrieved personal medical data to fuzzy personal medical data by using the self-learning artificial intelligence to determine a plurality of fuzzy attributes for the personal medical data, where a fuzzy attribute includes determining one or more fuzzy ranges of personal medical data values that are associated with discrete values or discrete ranges of the retrieved personal medical data,   analyzing the converted fuzzy personal medical data together with medical information retrieved by the saver over the communication network;   identifying at least one issue requiring follow-up by the patient or by at least one external authorized entity; and,   transmitting the issue, the related analyzed converted fuzzy personal medical data, and the medical information via the communication network to the at least one external authorized entity for follow-up analysis and treatment.   
     
     
         16 . The non-transitory storage medium of  claim 15 ,
 wherein a fuzzy range represents a variable range of values that are determined by the server using the self-learning artificial intelligence to incorporate acquired expert human judgement interpreting the discrete values and the discrete ranges, and defining their relationships to each other.   
     
     
         17 . The non-transitory storage medium of  claim 15 ,
 wherein the operations further include determining a plurality of fuzzy categories for the plurality of fuzzy attributes, wherein the fuzzy categories each have one or more fuzzy ranges that may overlap one another.   
     
     
         18 . The non-transitory storage medium of  claim 17 ,
 wherein the operations further include constructing a plurality of fuzzy functions corresponding to the plurality of fuzzy categories, wherein the plurality of fuzzy functions are constructed based on the plurality of fuzzy attributes and medical guideline data.   
     
     
         19 . The non-transitory storage medium of  claim 18 ,
 wherein the operations further include determining membership values in the plurality of fuzzy categories for the plurality of fuzzy attributes based on the plurality of fuzzy functions, and building a plurality of fuzzy tables for each of the plurality of fuzzy attributes.   
     
     
         20 . The non-transitory storage medium of  claim 18 ,
 wherein the self-learning artificial intelligence includes an artificial intelligence diagnosis protocol, an artificial intelligence therapy protocol, and an artificial intelligence inference engine.