HIV/AIDS

BioGAP-Ultra: A Modular Edge-AI Platform for Wearable Multimodal Biosignal Acquisition and Processing.

The growing demand for continuous physiological monitoring and human-machine interaction in real-world settings calls for wearable platforms that are flexible, low-power, and capable of on-device intelligence. This work presents BioGAP-Ultra, an advanced multimodal biosensing platform that supports synchronized acquisition of diverse electrophysiological and hemodynamic signals such as EEG, EMG, E...

A Comparative Evaluation of Large Language Models on Pediatric Board-Style Examinations.

OBJECTIVE: To evaluate the performance of 4 leading large language models (LLMs) on pediatric board-style examinations and to assess whether question characteristics are associated with response accuracy. METHODS: This study evaluated LLM platforms using the 2023 and 2024 editions of the American Academy of Pediatrics PREP® Self-Assessment. Under standardized testing conditions, all examination it...

PRIME: An evaluation framework for protein representation inference and generalization in viral mutation space.

BACKGROUND: Protein language models (PLMs) have revolutionized protein fitness prediction, yet their application to rapidly evolving viral pathogens i...

Bioinformatics analysis identifies biomarkers associated with T-cell depletion in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects multiple organ systems. In SLE, T-cell subsets are closely associated ...

M-Tune: imbalanced data handling in machine learning by tuning the decision threshold.

Overprediction of the majority class and poor predictive performance are the major issues when training machine learning classifiers with imbalanced d...

Deep learning approach for art style recognition and colour restoration in visual art images.

Color, as a core element in artistic images, not only contributes to visual aesthetics but also plays a crucial role in expressing emotions, construct...

Artificial intelligence and transforming cancer care.

Artificial Intelligence (AI) is reshaping oncology by addressing key limitations in traditional cancer care and enabling data-driven, personalized app...

RAS pathway activity subtypes identified by machine learning define prognostic and immune microenvironment characteristics in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, remains a leading cause of cancer-related ...

Machine learning models for predicting metabolic syndrome to support clinical decision-making in ART-treated adults living with HIV.

BACKGROUND: Metabolic syndrome (MetS) is an emerging complication among people living with HIV (PLHIV) receiving long-term antiretroviral therapy (ART...

Application of Sparse Autoencoders to Enhance Mechanistic Interpretability of Large Language Models in Medicine.

Large language models (LLMs) are being increasingly incorporated into clinical workflows due to their ability to synthesize medical knowledge and supp...

Predicting antifolate resistance in the unculturable fungal pathogen Pneumocystis jirovecii.

Pneumocystis jirovecii is an opportunistic fungal pathogen responsible for Pneumocystis pneumonia (PCP) in immunocompromised patients. Antifolate drug...

AI-Enhanced High-Precision Segmentation and Perfusion Analysis in Myocardial Contrast Echocardiography.

Myocardial contrast echocardiography (MCE) facilitates the quantification of myocardial perfusion and aids in diagnosing coronary artery disease (CAD)...

Using deep learning to identify brain networks mediating cognitive and motor impairments in alcohol use disorder.

Alcohol Use Disorder (AUD), with a lifetime prevalence of 29.1% in the U.S., is associated with functional impairment affecting visuospatial working m...

T-cell-mediated immunity to influenza A (H2N3): implications for caccine efficacy and cross-subtype protection.

Influenza A viruses pose a significant pandemic threat, with H2N3 in particular representing a subtype of particular concern due to limited population...

Identification of Lipid Metabolism-Related Gene GM2A as a Potential Biomarker in Atopic Dermatitis by Combining Weighted Gene Co-Expression Network Analysis and Machine Learning.

Lipid metabolism is abnormal in patients with atopic dermatitis (AD). This study aimed to screen lipid metabolism-related gene (LMRG) in AD, providing...

The intelligent ear: AI and hearing aids information seeking and users' discussion on social media.

OBJECTIVES: Hearing aids are the primary technology used to compensate for hearing loss, yet conventional signal treatment algorithms often fall short...

Phage ImmunoPrecipitation sequencing (PhIP-Seq) in autoimmunity research: From high-resolution epitope mapping to multi-omics integration.

Autoimmune diseases (AIDs) affect 5-10% of the global population, yet effective diagnosis and treatment remain challenging due to their complexity and...

Identification and analysis of oxidative stress-related genes associated with the occurrence and development of diabetic retinopathy.

Diabetic retinopathy (DR) develops via complex interactions of multiple risk factors and molecular pathways. However, the association between oxidativ...

Developing a Naïve Bayes risk classification machine learning algorithm to predict high viral load in a low-resource setting.

Access to routine viral load (VL) testing for people living with HIV (PLHIV) remains limited in many low-resource settings. There is a need for pragma...

Decoding the role of polyamine metabolism in lung adenocarcinoma prognosis: A triangulated approach combining transcriptome, single-cell and Mendelian randomization analyses.

The progression of lung adenocarcinoma (LUAD) is influenced by polyamine metabolism, which modulates antitumor immunity, although the underlying mecha...