HIV/AIDS

Application of Machine Learning for FOS/TAC Soft Sensing in Bio-Electrochemical Anaerobic Digestion.

This study explores the application of various machine learning (ML) models for the real-time prediction of the FOS/TAC ratio in microbial electrolysis cell anaerobic digestion (MEC-AD) systems using data collected during a 160-day trial treating brewery wastewater. This study investigated models including decision trees, XGBoost, support vector regression, a variant of support vector machine (SVM...

Study on the prediction performance of AIDS monthly incidence in Xinjiang based on time series and deep learning models.

OBJECTIVE: AIDS is a highly fatal infectious disease of Class B, and Xinjiang is a high-incidence region for AIDS in China. The core of prevention and control lies in early monitoring and early warning. This study aims to identify the best model for predicting the monthly AIDS incidence in Xinjiang, providing scientific evidence for AIDS prevention and control.

Using machine learning to predict poor adherence to antiretroviral therapy among adolescents with HIV in low resource settings.

OBJECTIVES: Achieving optimal adherence to antiretroviral therapy (ART) and viral suppression is still insufficient for attaining the UNAIDS 95-95-95 ...

Machine learning-based prediction model for patients with recurrent Staphylococcus aureus bacteremia.

BACKGROUND: Staphylococcus aureus bacteremia (SAB) remains a significant contributor to both community-acquired and healthcare-associated bloodstream ...

Machine learning-based characterization of PANoptosis-related biomarkers and immune infiltration in ulcerative colitis: A comprehensive bioinformatics analysis and experimental validation.

Ulcerative colitis (UC) is a heterogeneous autoimmune condition. PANoptosis, a new form of programmed cell death, plays a role in inflammatory disease...

Prioritizing Trust in Podiatrists' Preference for AI in Supportive Roles Over Diagnostic Roles in Health Care: Qualitative Interview and Focus Group Study.

BACKGROUND: As artificial intelligence (AI) evolves, its roles have expanded from helping out with routine tasks to making complex decisions, once the...

Predicting the Risk of HIV Infection and Sexually Transmitted Diseases Among Men Who Have Sex With Men: Cross-Sectional Study Using Multiple Machine Learning Approaches.

BACKGROUND: Men who have sex with men (MSM) are at high risk for HIV infection and sexually transmitted diseases (STDs). However, there is a lack of a...

IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition.

Deaf and hard-of-hearing people utilize sign language recognition (SLR) to interconnect. Sign language (SL) is vital for hard-of-hearing and deaf indi...

T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein-Ligand Binding Affinity Prediction with Uncertainty-Aware Self-Learning for Protein-Specific Alignment.

There is significant interest in targeting disease-causing proteins with small molecule inhibitors to restore healthy cellular states. The ability to ...

PBScreen: A server for the high-throughput screening of placental barrier-permeable contaminants based on multifusion deep learning.

Contaminants capable of crossing the placental barrier (PB) adversely affect female reproduction and fetal development. The rapid identification of PB...

Artificial intelligence in gastrointestinal cancer research: Image learning advances and applications.

With the rapid advancement of artificial intelligence (AI) technologies, including deep learning, large language models, and neural networks, these me...

Point-annotation supervision for robust 3D pulmonary infection segmentation by CT-based cascading deep learning.

Infected region segmentation is crucial for pulmonary infection diagnosis, severity assessment, and monitoring treatment progression. High-performance...

Future prospective of AI in drug discovery.

Drug discovery and development is very expensive and long with an inferior success rate. It is quite inefficient and costly due to huge R&D costs and ...

Two-stage CNN-based framework for leukocytes classification.

Leukocytes are pivotal markers in health, crucial for diagnosing diseases like malaria and viral infections. Peripheral blood smear tests provide path...

Radiomics in glioma: emerging trends and challenges.

Radiomics is a promising neuroimaging technique for extracting and analyzing quantitative glioma features. This review discusses the application, emer...

The Value of Artificial Intelligence in Prostate-Specific Membrane Antigen Positron Emission Tomography: An Update.

This review aims to provide an up-to-date overview of the utility of artificial intelligence (AI) in evaluating prostate-specific membrane antigen (PS...

The Emerging Influence of Artificial Intelligence on Traditional Medical Textbooks.

This review provides a comprehensive exploration of how artificial intelligence (AI) is reshaping medical education and the role of traditional textbo...

Pathogen genomic surveillance and the AI revolution.

The unprecedented sequencing efforts during the COVID-19 pandemic paved the way for genomic surveillance to become a powerful tool for monitoring the ...

Mental health phenotypes of well-controlled HIV in Uganda.

INTRODUCTION: The phenotypic expression of mental health (MH) conditions among people with HIV (PWH) in Uganda and worldwide are heterogeneous. Accord...

The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population-Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis.

BACKGROUND: HIV testing is the cornerstone of HIV prevention and a pivotal step in realizing the Joint United Nations Program on HIV/AIDS (UNAIDS) goa...