Machine learning-based profiles of atherosclerosis to predict disease outcomes in older HIV-infected women and men

Medicine & Life Sciences

1. Machine Learning 100%
2. Atherosclerosis 61%
3. HIV 52%
4. Phenotype 38%
5. HIV Infections 33%
6. Acquired Immunodeficiency Syndrome 21%
7. Cardiovascular Diseases 18%
8. Cohort Studies 17%
9. Epidemiologic Methods 17%
10. Critical Pathways 14%
11. Geriatrics 12%
12. Multicenter Studies 10%
13. Epidemiologic Studies 10%
14. Datasets 10%
15. Comorbidity 9%
16. Heart Failure 9%
17. Therapeutics 8%
18. Demography 8%
19. Inflammation 7%
20. Mortality 6%