Machine learning-based prediction of mortality risk in AIDS patients with comorbid common AIDS-related diseases or symptoms.

Journal: Frontiers in public health

PMID: 40144972

Abstract

OBJECTIVE: Early assessment and intervention of Acquired Immune Deficiency Syndrome (AIDS) patients at high risk of mortality is critical. This study aims to develop an optimally performing mortality risk prediction model for AIDS patients with comorbid AIDS-related diseases or symptoms to facilitate early intervention.

Authors

Yiwei Chen

Shanghai Synyi Medical Technology Co., Ltd, Shanghai, China.
Kejun Pan

Department of Infectious Diseases, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China.
Xiaobo Lu
Erxiding Maimaiti

Department of Epidemiology and Health Statistics, School of Public Health, Xinjiang Medical University, Urumqi, Xinjiang, China.
Maimaitiaili Wubuli

Department of Infectious Diseases, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China.

Keywords

Acquired Immunodeficiency Syndrome Adult Comorbidity Female Humans Machine Learning Male Middle Aged Risk Assessment ROC Curve

External Resources

View on PubMed Access via DOI PubMed (40144972)

Machine learning-based prediction of mortality risk in AIDS patients with comorbid common AIDS-related diseases or symptoms.

Abstract

Authors

Keywords

External Resources

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