Enhanced Language Models for Predicting and Understanding HIV Care Disengagement: A Case Study in Tanzania.

Journal: Research square
Published Date: May 8, 2025

Abstract

SUMMARY: Sustained engagement in HIV care and adherence to antiretroviral therapy (ART) are essential for achieving the UNAIDS "95-95-95" targets. Despite increased ART access, disengagement from care remains a significant issue, particularly in sub-Saharan Africa. Traditional machine learning (ML) models have shown moderate success in predicting care disengagement, which would enable early intervention. We develop an enhanced large language model (LLM) fine-tuned with electronic medical records (EMRs) to predict people at risk of disengaging from HIV care in Tanzania and to provide interpretative insights into modifiable risk factors.

Authors

  • Waverly Wei
    Division of Biostatistics, University of California, Berkeley, California, USA.
  • Junzhe Shao
    University of California, Berkeley.
  • Rita Qiuran Lyu
    University of California, Berkeley.
  • Rebecca Hemono
    University of California, Berkeley.
  • Xinwei Ma
    Department of Anesthesiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.
  • Joseph Giorgio
    Department of Psychology, University of Cambridge, Cambridge, United Kingdom.
  • Zeyu Zheng
    Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, PR China.
  • Feng Ji
    School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China. jifeng@tju.edu.cn.
  • Xiaoya Zhang
    Key Laboratory for Optoelectronic Technology and System of the Education Ministry of China, College of Optoelectronic Engineering, Chongqing University, Chongqing, China.
  • Emmanuel Katabaro
    Health for a Prosperous Nation, Dar es Salaam, Tanzania.
  • Matilda Mlowe
    Health for a Prosperous Nation, Dar es Salaam, Tanzania, United Republic of.
  • Amon Sabasaba
    Health for a Prosperous Nation, Dar es Salaam, Tanzania, United Republic of.
  • Caroline Lister
    Dodoma Referral Hospital, Dodoma, Tanzania.
  • Siraji Shabani
    United Republic of Tanzania Ministry of Health, Dodoma, Tanzania, United Republic of.
  • Prosper Njau
    Ministry of Health, Dodoma, Tanzania.
  • Sandra I McCoy
    School of Public Health, University of California, Berkeley, California, USA.
  • Jingshen Wang
    Division of Biostatistics, University of California, Berkeley, California, USA.

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