HIV/AIDS

Artificial intelligence-assisted analysis of musculoskeletal imaging-A narrative review of the current state of machine learning models.

The potential of Artificial intelligence (AI) is increasingly recognized in musculoskeletal radiolog...

Machine learning for personalized risk assessment of HIV, syphilis, gonorrhoea and chlamydia: A systematic review and meta-analysis.

BACKGROUND: Machine learning (ML) shows promise for sexually transmitted infection (STI) risk predic...

Unsupervised Accuracy Estimation for Brain-Computer Interfaces Based on Selective Auditory Attention Decoding.

OBJECTIVE: Selective auditory attention decoding (AAD) algorithms process brain data such as electro...

Significant associations between high-risk sexual behaviors and enterotypes of gut microbiome in HIV-negative men who have sex with men.

UNLABELLED: Gut microbiome of men who have sex with men (MSM) exhibits distinctive characteristics c...

AmesFormer: State-of-the-Art Mutagenicity Prediction with Graph Transformers.

The Ames mutagenicity test is a gold standard assay for the safety assessment of new chemicals. Howe...

Utilizing Machine Learning to Improve Neutralization Potency of an HIV-1 Antibody Targeting the gp41 N-Heptad Repeat.

The N-heptad repeat (NHR) of the HIV-1 gp41 prehairpin intermediate (PHI) is an attractive potential...

iAVP-RFVOT: Identify Antiviral Peptides by Random Forest Voting Machine Learning with Unified Manifold Learning Embedded Features.

Viruses are transmitted through multiple routes and can cause a wide range of diseases. Antiviral pe...

Artificial Intelligence to Improve Blood Pressure Control: A State-of-the-Art Review.

Hypertension remains a major global health challenge, contributing to significant morbidity and mort...

State-of-the-art analysis of electrocardiogram findings in sudden cardiac death.

Sudden cardiac death (SCD) is a significant public health issue, and efforts to prevent it have invo...

Current landscape and emerging opportunities for using telecytology for rapid on-site assessment in cytopathology.

In recent years, cytopathology practices increasingly are considering the adoption of digital modali...

AdaptFRCNet: Semi-supervised adaptation of pre-trained model with frequency and region consistency for medical image segmentation.

Recently, large pre-trained models (LPM) have achieved great success, which provides rich feature re...

Artificial intelligence in pediatric otolaryngology: A state-of-the-art review of opportunities and pitfalls.

BACKGROUND: Artificial Intelligence (AI) and machine learning (ML) have transformative potential in ...

Ternary spike-based neuromorphic signal processing system.

Deep Neural Networks (DNNs) have been successfully implemented across various signal processing fiel...

Hugan Tiaoshen Formula Improves the Comorbid Mechanism of Schizophrenia and Sleep Disorder via Multitarget Interaction Network.

This study aims to integrate cross-disease omics data and perform multidimensional analysis to uncov...

Assisted Reproductive Technology: A Ray of Hope for Infertility.

Assisted reproductive technologies (ART) have revolutionized the field of reproductive medicine, off...

SHAP-Driven Feature Analysis Approach for Epileptic Seizure Prediction.

Predicting epileptic seizures presents a substantial difficulty in healthcare, with considerable imp...

A comprehensive dataset of mandarin leaf images for classification.

The research is devoted to mandarin leaf classification using a deep learning approach. Citrus culti...

Meet the engineer using deep learning to restore Renaissance art.

A Combined-Mode Machine Learning Model for Predicting Stroke Recurrence During Hospitalization in Patients with Acute Minor Ischemic Stroke.

Acute minor ischemic stroke patients often experience recurrence shortly after symptom onset, highli...

Transcriptome Derived Artificial neural networks predict PRRC2A as a potent biomarker for epilepsy.

Epilepsy refers to the occurrence of two or more than two reiterative seizures. The occurrence of se...

Large language models in breast cancer reconstruction: A framework for patient-specific recovery and predictive insights.

Breast cancer reconstruction, a vital part of comprehensive cancer therapy, can be performed concurr...