Application of Machine Learning in Rheumatoid Arthritis Diseases Research:
Review and Future Directions

Aparna   Hiren   Patil Kose; Kiran      Mangaonkar
Abstract

Rheumatoid arthritis (RA) is a chronic, destructive condition that affects and destroys the joints of the hand, fingers, and legs. Patients may forfeit the ability to conduct a normal lifestyle if neglected. The requirement for implementing data science to improve medical care and disease monitoring is emerging rapidly as a consequence of advancements in computational technologies. Machine learning (ML) is one of these approaches that has emerged to resolve complicated issues across various scientific disciplines. Based on enormous amounts of data, ML enables the formulation of standards and drafting of the assessment process for complex diseases. ML can be expected to be very beneficial in assessing the underlying interdependencies in the disease progression and development of RA. This could perhaps improve our comprehension of the disease, promote health stratification, optimize treatment interventions, and speculate prognosis and outcomes.
Graphical Abstract

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Cite As
Combinatorial Chemistry & High Throughput Screening

Application of Machine Learning in Rheumatoid Arthritis Diseases Research: Review and Future Directions

Abstract

Graphical Abstract
