HIV/AIDS

Usability of a deep learning platform for detecting radiographic bone loss and furcation involvement.

BACKGROUND: Assessing radiographic bone condition is important for periodontal diagnosis. The accuracy of radiographic interpretation depends highly on a clinician's experience and knowledge. This study aimed to develop a deep learning-based online platform that aids clinicians in diagnosing periodontitis based on periapical radiographs and to evaluate the platform's usability using a validated su...

Rederived Closed-Form Continuous-Time Neural Networks.

In the field of machine learning, continuous-time neural networks (CTNNs) have garnered significant attention due to their powerful modeling capabilities for time series data. However, traditional numerical ordinary differential equation (ODE) solving methods suffer from computational inefficiency. Although closed-form CTNNs (CfCs) alleviate this issue through closed-form approximate solutions, th...

Machine learning prediction of weight gain after antiretroviral therapy initiation in people with HIV: Insights from a large french real-world cohort.

Excessive weight gain after initiation of antiretroviral therapy (ART) has become a recognized concern among people living with HIV. Individual weight...

Advances in the application of photodynamic diagnosis in Skin Tumors.

Photodynamic Diagnosis (PDD) is a non-invasive imaging technique. It relies on a photosensitizer that, when activated by a specific light source, caus...

Common factors and unique pathways for linkages between HIV/STI prevention and syndemic behaviours in high-risk youth: protocol for a secondary analysis of harmonised data from six clinical trials.

INTRODUCTION: HIV/sexually transmitted infection (STI) prevention interventions are only modestly successful among youth, particularly for young peopl...

A high density of T-cell lymphocytes and Tregs subset correlate to a worse survival in major salivary gland carcinomas.

Salivary gland carcinomas (SGC) are rare and heterogeneous tumors with limited therapeutic options in advanced stages. Recent evidence suggests a pote...

AI in Childbirth and Emerging Alternatives to Traditional Fertility Treatments.

Artificial Intelligence (AI) is revolutionizing reproductive medicine by enhancing fertility treatments, childbirth monitoring, and postnatal care. AI...

Advancing Global Nursing Policy: AI-Driven Health Literacy Innovations for Migrant Domestic Workers.

AIM: This perspective proposes evidence-informed strategies to advance health literacy equity for migrant domestic workers (MDWs) globally, integratin...

Deep-learning methods for contrast enhancement and artifact reduction in cryo-electron tomography: a systematic analysis of the state of the art and proposed improvements.

Cryo-electron tomography (cryo-ET) has emerged as the preferred technique for visualizing the organization of macromolecular complexes in situ and res...

Cancer-associated fibroblasts are associated with CD8+ T cell depletion and poor prognosis in colorectal adenocarcinoma: a multi-omics and machine learning analysis.

Fibroblastic proliferation in various tumor microenvironments influences cancer survival through complex interactions with diverse immune responses. T...

Multidimensional cfRNA response modeling identifies a 5-gene pair signature for high-robust pulmonary tuberculosis diagnosis.

Lack of non-invasive biomarkers hinders pulmonary tuberculosis (PTB) management. We developed a multidimensional machine learning framework to systema...

Machine learning-based MPPT integration with quadratic double-extended DC-DC converter for grid-connected PV-powered BLDC electric vehicles.

To mitigate the environmental challenges posed by pollution and climate change, researchers are increasingly focused on developing highly efficient, e...

Machine learning to optimize precision in the analysis of randomized trials: A journey in pre-specified, yet data-adaptive learning.

Covariate adjustment is an approach to improve the precision of trial analyses by adjusting for baseline variables that are prognostic of the primary ...

Identifying Subgroups of People Living With HIV in British Columbia, Canada Based on Sexually Transmitted and Blood-Borne Infection Testing and Diagnostic Laboratory Data: A Retrospective Cohort Study.

BACKGROUND AND AIMS: Although combination antiretroviral therapy has decreased morbidity and mortality in people living with HIV (PLWH), the prevalenc...

Visualization of Breast Reconstruction Outcomes Using an Artificial Intelligence-Enabled Simulator.

INTRODUCTION: Visual aids that simulate personalized postoperative outcomes following breast reconstruction may facilitate shared decision-making and ...

Present state and future of screening for atrial fibrillation: a state-of-the-art review.

Atrial fibrillation (AF) is the most common arrhythmia and is a leading cause of stroke and heart failure yet often remains undiagnosed. Screening has...

A dataset of midpalatal suture maturation stage in cone-beam computed tomography.

In the field of orthodontics, the degree of fusion of the midpalatal suture (MPS) is a crucial factor in determining the most appropriate maxillary ex...

AI-driven, low-cost aids for people with visual impairment.

PURPOSE OF REVIEW: The rapid integration of artificial intelligence (AI) into mainstream consumer devices has created new opportunities for accessible...

Simulated evaluation of large language model stepwise diagnostic reasoning with real-world chest pain encounters and Bayesian networks.

BACKGROUND: Real-world evaluation of large language models (LLMs) as clinical diagnostic aids is limited by the reliance on static vignettes and retro...

Screening Biomarkers for Nerve Injury Using Weighted Gene Co‐Expression Network Analysis and Machine Learning.

BACKGROUND: Nerve injury triggers complex molecular responses involving immune activation and neuronal damage, yet the key regulatory genes and their ...