Data-driven candidates predict the discovery of a future candidate for rheumatoid arthritis in the U

The concept of health management is increasingly widespread, and scientific health knowledge is gaining widespread attention. Rheumatoid arthritis (RA) is an autoimmune disease that mainly attacks the joints. Determining the prognostic factors for RA diagnosis may help in early diagnosis and prevention.

We applied a non-hypothesized, data-driven machine learning method that used data from 445,515 participants at the British Biobank, including 4,510 case-cases of events ((8. 4 years follow-up period, IQR 5. 3-10.

9))). Out of 2,898 basic input characteristics, identification as a potentially important characteristic by machine learning models was advanced to logical regression analysis and adjustment of known mixed factors. The model 3.

0-104. identifies 200 characteristics as potentially valuable for predicting the diagnosis of RA. Confirmation of historical joint disease, osteoporosis, decreased thyroid function, colorectal disease, and other joint disease-related factors is important for improving the level of early diagnosis and intervention of joint disease.

It should be noted that the above information is compiled on the basis of international public research, for reference in Health Cop, and does not constitute clinical advice. If you have any health questions, please consult professional medical professionals.