degninou/viral_ai: Codes for development and validation of AI-based prediction models for viral suppression in HIV care across five IeDEA West African countries (2019-2025)

degninou/VL_Suppression: Codes for development of algorithms for prediction of viral load suppression in an HIV patients cohort in Conakry, Republic of Guinea (Update)

No description provided.

degninou/viral_ai

Reproducible pipeline for predicting HIV viral suppression in five West African (IeDEA) countries, w

Codes for development of algorithms for prediction of viral load suppression in an HIV patients cohort in Conakry, Republic of Guinea

Viral load (VL) suppression represents a key to the end of the global HIV epidemic. It is critical f

Predicting HIV viral non-suppression in Uganda: development and validation of machine learning and risk stratification models using routine EMR data

Background Viral non-suppression is the primary actionable risk state in routi

Data Sheet 1_Predicting HIV viral non-suppression in Uganda: development and validation of machine learning and risk stratification models using routine EMR data.docx

Background

Viral non-suppression is the primary actionable risk state in routine HIV care, yet mos

Retention in Care and Viral Suppression in Differentiated Service Delivery Models for HIV Treatment in Sub-Saharan Africa: A Rapid Systematic Review

Introduction: Differentiated service delivery (DSD) models for antiretroviral treatment (ART) for HI