System Architecture for Digital Therapeutics with Drug Therapy for Precision and Personalized Care Pathway

Abstract

A system, method, and computer-readable medium are disclosed for processing patient related information in a health artificial intelligence system. patient answers are received to health symptom dialog questions and transformed into longitudinal data. The longitudinal data is stored as deep layer patient profile. Primary patient symptoms that are associated with detect knowledge models are processed as they relate to longitudinal data and deep layer patient profile. Laboratory results associated with diagnostic knowledge models are processed as related to the longitudinal data and deep layer patient profile. Physician results associated with diagnostic knowledge models are processed as related to the longitudinal data and deep layer patient profile. Recommendations are provided from the primary symptoms and laboratory results for addressing adverse events and related to the longitudinal data, deep layer patient profile, and knowledge models.

What is claimed is: 
     
         1 . A computer-implementable method of processing patient related information in a health artificial intelligence system comprising:
 receiving patient answers to health symptom dialog questions;   transforming the patient answers to longitudinal data;   storing the longitudinal data as a deep layer patient profile;   processing and presenting primary symptoms with associated detect knowledge models as related to the longitudinal data and deep layer patient profile;   processing and presenting laboratory results with associated diagnostic knowledge models as related to the longitudinal data and deep layer patient profile;   presenting physician results with associated diagnostic knowledge models as related to the longitudinal data and deep layer patient profile; and   providing recommendations from the primary symptoms and laboratory results for addressing adverse events and related to the longitudinal data, deep layer patient profile, and knowledge models.   
     
     
         2 . The computer-implementable method of  claim 1  further comprising sending questions to the patient for additional patient related information. 
     
     
         3 . The computer-implementable method of  claim 1 , wherein the patient answers are in response to modified dialog questions from detect and diagnose questions. 
     
     
         4 . The computer-implementable method of  claim 3 , wherein the modified dialog questions result from reducing conflicting questions, changing questions based on a specific genre question syntax, re-categorized and re-ordered questions based on priority resolution, and additional questions for subjective reduction. 
     
     
         5 . The computer-implementable method of  claim 1 , wherein the patient answers and health symptom dialog questions are presented through a user interface, audio input and output, camera input and output, and gesture input and output. 
     
     
         6 . The computer-implementable method of  claim 1 , wherein the recommendations are derived from algorithms that use the patient answers, the laboratory results and the knowledge models. 
     
     
         7 . The computer-implementable method of  claim 1 , wherein the primary symptoms are produced from algorithms using patient reported symptoms and the knowledge models. 
     
     
         8 . The computer-implementable method of  claim 1 , wherein the recommendations are derived by algorithms that use detect and diagnosis results, and produced preliminary diagnosis, priorities and weights. 
     
     
         9 . The computer-implementable method of  claim 1  further comprising providing natural language patient reported symptom, disambiguating patient reported outcomes with dialog techniques, and producing a numerical longitudinal mapping for structured and deep layer patient profile storage. 
     
     
         10 . The computer-implementable method of  claim 1 , wherein the method is used for multiple domains, programs, diseases, symptoms, subject matter expert knowledge models for Dialog, Transform, Detect, Diagnose, Recommend, weight, priorities and genres. 
     
     
         11 . A system comprising:
 a processor;   a data bus coupled to the processor; and   a non-transitory, computer-readable storage medium embodying computer program code, the non-transitory, computer-readable storage medium being coupled to the data bus, the computer program code interacting with a plurality of computer operations and comprising instructions executable by the processor and configured for:
 receiving patient answers to health symptom dialog questions; 
 transforming the patient answers to longitudinal data; 
 storing the longitudinal data as a deep layer patient profile; 
 processing and presenting primary symptoms with associated detect knowledge models as related to the longitudinal data and deep layer patient profile; 
 processing and presenting laboratory results with associated diagnostic knowledge models as related to the longitudinal data and deep layer patient profile; 
 presenting physician results with associated diagnostic knowledge models as related to the longitudinal data and deep layer patient profile; and 
 providing recommendations from the primary symptoms and laboratory results for addressing adverse events and related to the longitudinal data, deep layer patient profile, and knowledge models. 
   
     
     
         12 . The system of  claim 11  further comprising sending questions to the patient for additional patient related information. 
     
     
         13 . The system of  claim 11 , wherein the patient answers are in response to modified dialog questions from detect and diagnose questions. 
     
     
         14 . The system of  claim 13 , wherein the modified dialog questions result from reducing conflicting questions, changing questions based on a specific genre question syntax, re-categorized and re-ordered questions based on priority resolution, and additional questions for subjective reduction. 
     
     
         15 . The system of  claim 11 , wherein the patient answers and health symptom dialog questions are presented through a user interface, audio input and output, camera input and output, and gesture input and output. 
     
     
         16 . The system of  claim 11 , wherein the recommendations are derived from algorithms that use the patient answers, the laboratory results and the knowledge models. 
     
     
         17 . The system of  claim 11 , wherein the primary symptoms are produced from algorithms using patient reported symptoms and the knowledge models. 
     
     
         18 . The system of  claim 11 , wherein the recommendations are derived by algorithms that use detect and diagnosis results, and produced preliminary diagnosis, priorities and weights. 
     
     
         19 . The system of  claim 11  further comprising providing natural language patient reported symptom, disambiguating patient reported outcomes with dialog techniques, and producing a numerical longitudinal mapping for structured and deep layer patient profile storage. 
     
     
         20 . The system of  claim 11 , wherein the method is used for multiple domains, programs, diseases, symptoms, subject matter expert knowledge models for Dialog, Transform, Detect, Diagnose, Recommend, weight, priorities and genres. 
     
     
         21 . A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for:
 receiving patient answers to health symptom dialog questions;   transforming the patient answers to longitudinal data;   storing the longitudinal data as a deep layer patient profile;   processing and presenting primary symptoms with associated detect knowledge models as related to the longitudinal data and deep layer patient profile;   processing and presenting laboratory results with associated diagnostic knowledge models as related to the longitudinal data and deep layer patient profile;   presenting physician results with associated diagnostic knowledge models as related to the longitudinal data and deep layer patient profile; and   providing recommendations from the primary symptoms and laboratory results for addressing adverse events and related to the longitudinal data, deep layer patient profile, and knowledge models.   
     
     
         22 . The non-transitory, computer-readable storage medium of  claim 21  further comprising instructions for sending questions to the patient for additional patient related information. 
     
     
         23 . The non-transitory, computer-readable storage medium of  claim 21 , wherein the patient answers are in response to modified dialog questions from detect and diagnose questions. 
     
     
         24 . The non-transitory, computer-readable storage medium of  claim 23 , wherein the modified dialog questions result from reducing conflicting questions, changing questions based on a specific genre question syntax, re-categorized and re-ordered questions based on priority resolution, and additional questions for subjective reduction. 
     
     
         25 . The non-transitory, computer-readable storage medium of  claim 15  wherein are refined based on determinative factors related to the patient. 
     
     
         26 . The non-transitory, computer-readable storage medium of  claim 15  wherein the digital therapeutics is related to oncology immunotherapy treatment. 
     
     
         27 . The non-transitory, computer-readable storage medium of  claim 21 , wherein the patient answers and health symptom dialog questions are presented through a user interface, audio input and output, camera input and output, and gesture input and output. 
     
     
         28 . The non-transitory, computer-readable storage medium of  claim 21 , wherein the recommendations are derived by algorithms that use detect and diagnosis results, and produced preliminary diagnosis, priorities and weights. 
     
     
         29 . The non-transitory, computer-readable storage medium of  claim 21  further comprising instructions for providing natural language patient reported symptom, disambiguating patient reported outcomes with dialog techniques, and producing a numerical longitudinal mapping for structured and deep layer patient profile storage. 
     
     
         30 . The non-transitory, computer-readable storage medium of  claim 21 , wherein the method is used for multiple domains, programs, diseases, symptoms, subject matter expert knowledge models for Dialog, Transform, Detect, Diagnose, Recommend, weight, priorities and genres.