Predictive Clinical Diagnosis of Rheumatoid Arthritis Flares Using Non-Invasive Infra-red Thermal Imaging and an AI/ML Algorithm

Objective #1: To assess the clinical feasibility of implementing a novel, physician assisting, diagnostic approach for RA when compared to conventional RA examination and diagnostic procedures.

This prospective, non-interventional study will assess clinically assess and diagnose the severity of RA in sero-positive RA patients experiencing active flares by using conventional examination and diagnostic methods, and compared those with a physician-assisting, diagnostic approach that involves the use of an infrared thermal imaging device, which detects heat waves to be correlated between RA patients and control subjects (i.e., those who do not have RA or who are in remission). Standard clinical laboratory values will be documented from the EHR system as well and will include ESR (sedimentation rate) and CRP (c-reactive protein).

Objective #2: To develop and optimize a ML/Artificial intelligence(AI) algorithm that would process and analyze thermal images and assist in the predictive diagnosis of RA using the DAS-28 ESR score for those thermal images of the inflamed joints of patients.

This study will predict the probability of an actual flare occurrence and its severity in RA patients by using an optimized, physician assisting ML/AI algorithm that processes and analyzes thermal images from sero-positive RA patients in pain and experiencing flares and that calculates the DAS-28 scoring system in real-time