التفاصيل البيبلوغرافية
| العنوان: |
Machine Learning in Rheumatic Diseases. |
| المؤلفون: |
Jiang, Mengdi, Li, Yueting, Jiang, Chendan, Zhao, Lidan, Zhang, Xuan, Lipsky, Peter E |
| المصدر: |
Clinical Reviews in Allergy & Immunology; 2021, Vol. 60 Issue 1, p96-110, 15p |
| مستخلص: |
With advances in information technology, the demand for using data science to enhance healthcare and disease management is rapidly increasing. Among these technologies, machine learning (ML) has become ubiquitous and indispensable for solving complex problems in many scientific fields, including medical science. ML allows the development of guidelines and framing of the evaluation system for complex diseases based on massive data. In the analysis of rheumatic diseases, which are chronic and remarkably heterogeneous, ML can be anticipated to be extremely helpful in deciphering and revealing the inherent interrelationships in disease development and progression, which can further enhance the overall understanding of the disease, optimize patients' stratification, calibrate therapeutic strategies, and predict prognosis and outcomes. In this review, the basics of ML, its potential clinical applications in rheumatology, together with its strengths and limitations are summarized. [ABSTRACT FROM AUTHOR] |
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Copyright of Clinical Reviews in Allergy & Immunology is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| قاعدة البيانات: |
Complementary Index |
