HIV/AIDS

PhyloCNN: Improving Tree Representation and Neural Network Architecture for Deep Learning from Trees in Phylodynamics and Diversification Studies.

Phylodynamics and diversification studies using complex evolutionary models can be challenging, especially with traditional likelihood-based approaches. As an alternative, likelihood-free simulation-based approaches have been proposed due to their ability to incorporate complex models and scenarios. Here, we propose a new simulation-based deep learning (DL) method capable of selecting birth-death ...

MoADL-TLSTM: Multiobjective Automated Deep Learning-Based Transformer-LSTM for Load Forecasting.

Accurate load forecasting serves as the critical factor for optimizing energy allocation and ensuring economic operation in cyber-physical power systems (CPPSs). Deep learning (DL) models have emerged as pivotal tools for capturing complex temporal patterns for enhancing the performance of load forecasting. However, the existing DL-based load forecasting models contain some shortcomings such as pr...

HIV-1 protease cleavage sites detection with a quantum convolutional neural network algorithm.

Human immunodeficiency virus type 1 (HIV-1) protease plays a crucial role in viral maturation by cleaving both viral and host precursor proteins. Accu...

Integrative transcriptomic and machine learning analysis identifies key extracellular matrix-related genes in diabetic retinopathy.

Extracellular matrix (ECM) remodeling contributes to retinal vascular basement membrane thickening, an early structural hallmark of diabetic retinopat...

Peripheral and central immune features in insomnia: Integrative bulk and single-cell transcriptomic analyses reveal core hub genes and candidate compounds.

Insomnia is closely associated with immune dysregulation, yet the overall pattern of peripheral-central immune disequilibrium and its underlying molec...

Geospatial variation and machine learning approaches to predict open defecation practice in Zambia.

BACKGROUND: Open defecation is the disposal of human feces in fields, bushes, forests, open waterways, beaches, and other open areas. It worsens the e...

Identifying communities at elevated risk of hepatitis C infection in Los Angeles County: an ecological study using machine learning.

BACKGROUND: Identifying communities disproportionately affected by hepatitis C infection is essential for targeted prevention and resource allocation....

Predictors of Detectable Viral Load among Adolescents with HIV in Low Resource Settings who are Receiving Care in Youth-Friendly Clinics.

OBJECTIVE: Adolescents with HIV (AWH) have higher rates of detectable viral loads (DVL) than adults. We sought to identify clinical and psychosocial p...

Rehabilitation Protocols Following Patellar Instability Surgery: A Structured Review of Published Recommendations and AI Generated Guidance.

PURPOSE OF REVIEW: To review postoperative rehabilitation protocols after surgery for patellar instability, including medial patellofemoral ligament r...

Integrated transcriptomics, network pharmacology and clinical expression validation reveal the prognostic significance of PANoptosis-related genes in cordycepin-treated lung adenocarcinoma.

BACKGROUND: Studies have shown that PANoptosis is increasingly involved in cancer and cancer treatment. The Cordycepin has also been found to be invol...

Tuberculosis in households with infectious cases in Kampala city: Harnessing health data science for new insights on an ancient disease with persistent, unresolved problems.

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...

pedQTNet: A Deep Learning Approach to Estimate Corrected QT Intervals from Multi-Lead Conventional ECG Waveforms in Pediatric Patients.

Long QT syndrome (LQTS) is a primary risk factor for ventricular arrhythmias and sudden cardiac death in children. Accurate corrected QT intervals (QT...

Evaluation of large language models in terms of safety, contraindications, and adverse effect information related to botulinum toxin applications.

BACKGROUND: Large language models (LLMs) are increasingly used for the dissemination of health-related information. However, data regarding the accura...

DG-LSTM-SA model: A deep gated LSTM network with self-attention mechanism for power generation and load forecasting.

Accurate forecasting of power generation and load demand is essential for the reliable operation of modern energy systems. Traditional recurrent neura...

Predicting knowledge of cervical cancer screening among reproductive-age women in sub-saharan africa using machine learning algorithms.

Sub-Saharan Africa faces twice the incidence and up to fifteen times the fatality rate of cervical cancer compared to developed countries. Screening c...

Transcriptome sequencing combined with experimental verification to explore potential key genes related to uric acid in diabetic retinopathy.

PURPOSE: Diabetic retinopathy (DR), a major microvascular complication of diabetes and leading global blindness cause, involves uric acid (UA) in its ...

Development and Implementation of a Machine Learning Model for Prediction of Surgical Case Duration.

BACKGROUND: Accurate surgical case duration estimation (CDE) is critical for operating room efficiency, staffing, resource allocation, and patient saf...

Attention-Guided Multi-View Contrastive Learning for Predicting Sparse Drug-Gene Associations.

Employing deep learning techniques for drug discovery and repurposing necessitates the acceleration of predictions regarding drug-gene interactions. H...

Characterizing Central-Autonomic Dynamics During an Episodic Memory Task Using Multi-Modal Neural and Cardiomechanical Signals.

OBJECTIVE: Memory function underlies mental and behavioral health. While the role of the central nervous system (CNS) during episodic memory encoding ...

An Active Dry-Contact Continuous EEG Monitoring System for Seizure Detection Applications in Clinical Neurophysiology.

OBJECTIVE: Young children and infants, especially newborns, are highly susceptible to seizures, which, if undetected and untreated, can lead to severe...