HIV/AIDS

Pediatric HIV Hotspots in Kenya: Machine Learning and Geostatistical Analysis for Enhanced Case Finding

Background Although Kenya's HIV programme has long prioritized high-burden counties for intensified paediatric interventions, a critical evidence gap remains in developing integrated analytic frameworks that can objectively predict and validate paediatric HIV burden using data-driven models. We therefore developed and tested a framework that combines machine-learning (ML) prediction with geostatis...

Tuberculosis in households with infectious cases in Kampala city: Harnessing health data science for new insights on an ancient disease with persistent, unresolved problems (DS-IAFRICA TB) study protocol

Tuberculosis (TB) is prevalent in Uganda and overlaps with a high rate of HIV/TB coinfection. While nearly all hospital-based TB cases in Kampala, the capital of Uganda, show clear TB symptoms, 30% or more of undiagnosed TB cases found through active screening are asymptomatic. Additionally, the host risk factors for TB in Kampala cannot be distinguished from environmental risk factors. These TB-s...

Identify Patients at Risk of HIV Using a Clinical Large Language Model from Electronic Health Records

This study developed a large language model (LLM)-based solution to identify people at HIV risk using electronic health records. We transformed struct...

Mass cytometry data integration methods reveal rural-urban gradient of immune profiles across geography

The human immune system strongly varies across populations and is shaped by a wide range of host and environmental factors. As such, a rural compared ...

Quality-Aware Calibration for AI-Generated Image Detection in the Wild

Significant progress has been made in detecting synthetic images, however most existing approaches operate on a single image instance and overlook a k...

Explainable Fall Detection for Elderly Care via Temporally Stable SHAP in Skeleton-Based Human Activity Recognition

Fall detection in elderly care requires not only accurate classification but also reliable explanations that clinicians can trust. However, existing p...

Sparse Hypergraph-Enhanced Frame-Event Object Detection with Fine-Grained MoE

Integrating frame-based RGB cameras with event streams offers a promising solution for robust object detection under challenging dynamic conditions. H...

AbLWR:A Context-Aware Listwise Ranking Framework for Antibody-Antigen Binding Affinity Prediction via Positive-Unlabeled Learning

Accurate prediction of antibody-antigen binding affinity is fundamental to therapeutic design, yet remains constrained by severe label sparsity and th...

Uncertainty-Guided Attention and Entropy-Weighted Loss for Precise Plant Seedling Segmentation

Plant seedling segmentation supports automated phenotyping in precision agriculture. Standard segmentation models face difficulties due to intricate b...

DeepBranchAI: A Novel Cascade Workflow Enabling Accessible 3D Branching Network Segmentation

Three-dimensional branching networks exist throughout biological, natural, and man-made systems as pathways through volumetric space. Segmentation is ...

Federated Learning Performance Depends on Site Variation in Global HIV Data Consortia

Digital health technologies, including machine learning (ML), are transforming infectious disease management, however ML models for HIV care have been...

Utility of 3D Facial Analysis As A Biomarker In Rare Diseases Exploration with Hereditary Angioedema

Importance: People living with rare diseases (PLWRD) often face significant challenges in receiving timely and accurate diagnoses, leading to what is ...

The Gait Signature of Frailty: Transfer Learning based Deep Gait Models for Scalable Frailty Assessment

Frailty is a condition in aging medicine characterized by diminished physiological reserve and increased vulnerability to stressors. However, frailty ...

ARGENT: Adaptive Hierarchical Image-Text Representations

Large-scale Vision-Language Models (VLMs) such as CLIP learn powerful semantic representations but operate in Euclidean space, which fails to capture ...

HViLM: A Foundation Model for Viral Genomics Enables Multi-Task Prediction of Pathogenicity, Transmissibility, and Host Tropism

Motivation: The emergence of novel viral pathogens poses critical threats to global health, yet current computational approaches for viral risk assess...

X-Cell: Scaling Causal Perturbation Prediction Across Diverse Cellular Contexts via Diffusion Language Models

Causal models of cellular systems hold the promise to empower broad biological discovery, including the systematic identification of novel targets for...

The results of Transcriptome-wide Mendelian Randomization (TWMR) in large-scale populations can directly validate, across scales, the results of causal inference from deep learning combined with double machine learning on single-cell transcriptomes of human samples.

Objective Aiming at the core problems prevalent in biomedical research, including the "translational distance", the difficulty in aligning cross-scale...

From Carb Counting to Diagnosis: Real World Patient Uses and Attitudes Toward Large Language Models in Diabetes Management

Managing diabetes-related conditions is time-intensive and cognitively demanding for patients and caregivers, requiring ongoing glucose monitoring, di...

PCA-Enhanced Probabilistic U-Net for Effective Ambiguous Medical Image Segmentation

Ambiguous Medical Image Segmentation (AMIS) is significant to address the challenges of inherent uncertainties from image ambiguities, noise, and subj...

PCA-Enhanced Probabilistic U-Net for Effective Ambiguous Medical Image Segmentation

Ambiguous Medical Image Segmentation (AMIS) is significant to address the challenges of inherent uncertainties from image ambiguities, noise, and subj...