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Can machine learning unravel the complex IIM spectrum?
- Source :
- Lilleker, J B & Chinoy, H 2020, ' Can machine learning unravel the complex IIM spectrum? ', Nature Reviews Rheumatology . https://doi.org/10.1038/s41584-020-0412-6
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- Idiopathic inflammatory myopathies (IIMs) are heterogeneous conditions, and the optimal way to classify patients and divide them into subgroups remains unclear. Could machine learning techniques be the answer to the problem of defining homogeneous disease phenotypes, enabling stratified treatment approaches and the formulation of future IIM classification criteria?
- Subjects :
- 030203 arthritis & rheumatology
0301 basic medicine
business.industry
Machine learning
computer.software_genre
Spectrum (topology)
03 medical and health sciences
030104 developmental biology
0302 clinical medicine
Idiopathic inflammatory myopathies
Rheumatology
Homogeneous
Medicine
Artificial intelligence
business
Clinical phenotype
computer
Subjects
Details
- ISSN :
- 17594804 and 17594790
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- Nature Reviews Rheumatology
- Accession number :
- edsair.doi.dedup.....e2dbfaec954536e41233ce319523d66e
- Full Text :
- https://doi.org/10.1038/s41584-020-0412-6