# US 2021/0343384 A1 · Systems and methods for managing autoimmune conditions, disorders and diseases > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0343384 A1 - Document ID: US20210343384A1 - Status: Published application - Kind: A1 - Application number: 16/866,498 - Filed: 2020-05-04 - Published: 2021-11-04 - Earliest claimed: 2020-05-04 - Assignees: Progentec Diagnostics, Inc. - Applicants: Progentec Diagnostics, Inc. - Inventors: Mohan Purushothaman; Arif Latif Sorathia - Web page: https://patentgrep.com/patent/US20210343384A1 ## CPC - G16H 20/10: relating to drugs or medications, e.g. for ensuring correct administration to patients - G06N 3/044: Recurrent networks, e.g. Hopfield networks - G06N 3/0442: characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU] - G06N 3/045: Combinations of networks - G06N 3/0464: Convolutional networks [CNN, ConvNet] - G06N 3/0475: Generative networks - G06N 3/08: Learning methods - G06N 3/084: Backpropagation, e.g. using gradient descent - G06N 3/09: Supervised learning - G06N 3/094: Adversarial learning - G06N 20/00: Machine learning - G16B 40/20: Supervised data analysis - G16H 10/60: for patient-specific data, e.g. for electronic patient records - G16H 15/00: ICT specially adapted for medical reports, e.g. generation or transmission thereof - G16H 40/67: for remote operation - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - G16H 80/00: ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring - G06N 5/01: Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY ## Abstract An artificial intelligence (AI) system and methods for management of an autoimmune or inflammatory condition, disorder or disease in a patient for the diagnosis, prognosis, or risk assessment of symptoms thereof. The AI system includes patient and provider applications and a payer application interface accessible via a communications network. The system contains a data-driven recommendation engine using machine learning and/or deep learning based on active monitoring of patients with an autoimmune or inflammatory-related condition, disorder, or disease. The system can alert clinicians to an impending symptom flare and provide a treatment solution that reduces symptom severity, reduces or eliminates the onset. ## Claims ### Claim 1 A computer-implemented method for evaluation or management of an autoimmune condition, the method comprising: receiving, with a mobile electronic device, a first plurality of data comprising one or more user-generated inputs corresponding to an autoimmune condition of a patient user; receiving, with the mobile electronic device, a second plurality of data comprising at least one physiological measurement associated with the patient user; receiving, with a processor, the first plurality of data and the second plurality of data from the mobile electronic device, and a third plurality of data from at least one external data source comprising an electronic medical record system or laboratory information management system; aggregating, with the processor, the first plurality of data, the second plurality of data, and the third plurality of data to define an aggregated dataset; analyzing, with the processor, the aggregated dataset according to at least one machine learning framework comprising at least one supervised learning model or artificial neural network, wherein the at least one machine learning framework comprises at least one dependent variable corresponding to a current or future state of the autoimmune condition; generating, with the processor, at least one diagnostic measure of the current or future state of the autoimmune condition according to the at least one machine learning framework; and generating, with the processor, at least one activity recommendation in response to the at least one diagnostic measure, the at least one activity recommendation corresponding to at least one patient outcome associated with the current or future state of the autoimmune condition. ### Claim 2 (depends on 1) The method of claim 1 further comprising providing, with the processor, the at least one diagnostic measure and the at least one activity recommendation to a provider user. ### Claim 3 (depends on 1) The method of claim 1 further comprising receiving, with the mobile electronic device, a fourth plurality of data comprising one or more user-generated inputs corresponding to at least one patient-reported outcome in response to the at least one activity recommendation. ### Claim 4 (depends on 3) The method of claim 3 further comprising analyzing, with the processor, the at least one patient-reported outcome to determine a measure of efficacy of the at least one activity recommendation. ### Claim 5 (depends on 1) The method of claim 1 wherein the at least one activity recommendation comprises a recommended pharmacological intervention comprising a recommended dosage and timing of at least one of a nonsteroidal anti-inflammatory drug, an immunosuppressive drug, and a steroid. ### Claim 6 (depends on 1) The method of claim 1 wherein the at least one activity recommendation comprises a recommended non-pharmacological intervention comprising a recommended UV exposure mitigation action or recommended activity modification. ### Claim 7 (depends on 3) The method of claim 3 further comprising providing, with the processor, the at least one diagnostic measure, the at least one activity recommendation, and the at least one patient-reported outcome to a provider user. ### Claim 8 (depends on 1) The method of claim 1 wherein the at least one activity recommendation comprises a recommended laboratory diagnostic procedure comprising an antibody test. ### Claim 9 (depends on 1) The method of claim 1 wherein the at least one physiological measurement comprises a sensor input from a wearable electronic device. ### Claim 10 A system for predictive screening or management of an autoimmune condition, the system comprising: a mobile electronic device configured to execute an instance of a graphical user interface comprising a plurality of user prompts associated with an autoimmune condition of a patient user; an integral or remote processor communicatively engaged with the mobile electronic device; and a non-transitory computer readable medium having instructions stored thereon that, when executed, cause the processor to perform one or more operations, the one or more operations comprising operations for: receiving a plurality of user-generated inputs in response to the plurality of user prompts; receiving one or more sensor inputs comprising a patient activity input or a patient physiological input; receiving one or more external data inputs comprising at least one patient historical data input; aggregating the plurality of user-generated inputs, the one or more sensor inputs, and the one or more external data inputs to define an aggregated dataset; analyzing the aggregated dataset according to at least one machine learning framework comprising at least one supervised learning model or artificial neural network, wherein the at least one machine learning framework comprises at least one dependent variable corresponding to a current or future state of the autoimmune condition; generating at least one diagnostic measure of the current or future state of the autoimmune condition according to the at least one machine learning framework; and generating, with the processor, at least one activity recommendation in response to the at least one diagnostic measure, the at least one activity recommendation corresponding to at least one patient action associated with the current or future state of the autoimmune condition. ### Claim 11 (depends on 10) The system of claim 10 further comprising at least one wearable electronic device being communicatively engaged with the processor, the at least one wearable electronic device comprising at least one sensor being configured to receive the patient activity input or the patient physiological input. ### Claim 12 (depends on 10) The system of claim 10 wherein the plurality of user-generated inputs comprises one or more patient-reported outcomes in response to the at least one activity recommendation. ### Claim 13 (depends on 10) The system of claim 10 wherein the one or more external data inputs comprise at least one environmental condition corresponding to a location of the patient user, the at least one environmental condition comprising a UV index. ### Claim 14 (depends on 12) The system of claim 12 wherein the one or more operations further comprise operations for analyzing the aggregated dataset to generate one or more patient outcome metrics associated with the autoimmune condition of the patient user. ### Claim 15 (depends on 10) The system of claim 10 wherein the at least one patient historical data input comprises electronic medical record data or laboratory diagnostic data. ### Claim 16 (depends on 10) The system of claim 10 wherein the one or more operations further comprise operations for providing a communications interface between the mobile electronic device and a provider client device or a health coach client device. ### Claim 17 (depends on 14) The system of claim 14 wherein the one or more operations further comprise operations for communicating the one or more patient outcome metrics to a provider user. ### Claim 18 (depends on 14) The system of claim 14 wherein the one or more operations further comprise operations for communicating the one or more patient outcome metrics to a payor user. ### Claim 19 (depends on 10) The system of claim 10 wherein the at least one activity recommendation comprises at least one of a recommended pharmacological intervention, a recommended non-pharmacological intervention, and a laboratory diagnostic procedure. ### Claim 20 A non-transitory computer-readable medium encoded with instructions for commanding one or more processors to execute operations of a method for predictive screening or management of an autoimmune condition, the operations comprising one or more operations for: receiving a plurality of data from one or more data sources, the plurality of data comprising one or more user-generated inputs corresponding to an autoimmune condition in a patient user; aggregating the plurality of data to define an aggregated dataset; analyzing the aggregated dataset according to at least one machine learning framework comprising at least one supervised learning model or artificial neural network, wherein the at least one machine learning framework comprises at least one dependent variable corresponding to a current or future state of the autoimmune condition; generating at least one diagnostic measure of the autoimmune condition according to the at least one machine learning framework; and generating at least one activity recommendation in response to the at least one diagnostic measure, the at least one activity recommendation corresponding to at least one patient outcome associated with the current or future state of the autoimmune condition.