Tuberculosis

Correction: TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations.

Exploring tuberculosis physicians' preferences for AI explainability in China: a protocol for a discrete choice experiment.

INTRODUCTION: Artificial intelligence (AI) is increasingly used in tuberculosis (TB) diagnosis, but its clinical adoption depends not only on accuracy but also on physicians' trust and understanding of AI outputs. Explainable AI (XAI) has been proposed to address this challenge, but limited evidence exists on which explanation features are most valued by physicians in TB diagnostic settings. Discr...

An Aging Clock Based on Immune Repertoire Features: COVID-19 Accelerates Aging.

Aging induces immunosenescence, a progressive decline in immune function underpinning age-related pathogen vulnerability, yet T/B cell receptor (TCR/B...

Identification of chemical features for improved outer membrane permeation in mycobacteria using machine learning.

The ability of compounds to permeate and accumulate in bacterial cells is a critical determinant of antibiotic efficacy. Better therapeutics are urgen...

A smear test aiding with an automated slide reader acquires equivalent sensitivity to MGIT960 culture in pulmonary tuberculosis diagnosis.

UNLABELLED: Smear microscopy remains widely used for tuberculosis (TB) diagnosis due to its rapid turnaround and low cost, despite its relatively low ...

Diagnosing lung disorder and optimal classification using dense convolution (Dc)-CapsNet technique.

Lung carcinoma is regarded as lung cancer and is the usual form of cancers worldwide. It cannot be diagnosed easily until it spreads and is regarded a...

Artificial intelligence-based prediction of diseases among homeless populations in Bogotá: Implications for targeted interventions.

BACKGROUND: The homeless population in Bogotá exhibits complex social and health vulnerabilities, with a high prevalence of chronic and communicable d...

Development and validation of machine-learning diagnostic models for identifying frailty in older adults with tuberculosis: a multicentre observational study protocol.

BACKGROUND: The Frailty in Tuberculosis (FIT) study aims to assess frailty in older adults with tuberculosis (TB) using machine learning (ML) to devel...

Cough biomarkers for diagnosis and monitoring of respiratory disease: a systematic review.

Cough is a common and physiologically informative component of respiratory morbidity, but its potential for diagnosing and monitoring disease is not t...

Transformer-accelerated discovery of inhibitors targeting the RpsAΔ438 deletion in PZA-resistant tuberculosis.

Tuberculosis is a major global public health problem caused by Mycobacterium tuberculosis. Pyrazinamide (PZA), a key first-line drug, is activated to ...

Integrative single-cell profiling and explainable AI identify monocyte-metabolic signatures as diagnostic biomarkers and candidate therapeutic targets in tuberculosis.

Tuberculosis (TB) remains a formidable global health threat, yet rapid and accurate diagnostic biomarkers capturing host immune-metabolic dysregulatio...

Artificial Intelligence in Pediatric Imaging: A Primer for Pediatric Clinicians.

Artificial intelligence (AI) is reshaping healthcare, and radiology is at the forefront for adoption. Increasing demand for imaging, complex protocols...

Patient centered and technology enabled strategies to improve Tuberculosis treatment adherence.

INTRODUCTION: Tuberculosis (TB) treatment adherence (how regular patients follow the prescribed medication) has a major role in TB control. In high bu...

Development and validation of artificial intelligence-assisted volumetric response criteria in pleural mesothelioma (ARTIMES): a retrospective, multicohort, multicentre study.

BACKGROUND: Response evaluation in pleural mesothelioma is challenging because its crescent growth pattern is poorly captured by diameter-based criter...

LXNet: A lightweight CNN for lung disease classification from Chest X-ray with XAI-based interpretability.

The diagnosis of lung diseases such as pneumonia and tuberculosis remains a major global health challenge, especially in resource-limited regions. Art...

An Aptamer-Engineered Phenotyping System for Extracellular Vesicles Based on Honeycomb-like Melamine-Formaldehyde Microspheres and Carbon Dot Nanozymes.

Molecular phenotyping of extracellular vesicles (EVs) holds promise for noninvasive cancer diagnosis; however, current methodologies encounter limitat...

High-resolution nanopore peptide sensing, profiling and sequence assembly.

Nanopores have been explored as a potential platform for protein analysis following the success of nanopore nucleic acid sequencing. However, protein ...

The current state of demographic subgroup reporting for commercially available AI for radiology: a scoping review.

OBJECTIVE: Though subgroup performance reporting helps ensure the safety of artificial intelligence (AI) products, the extent of this reporting remain...

Identification of Novel Diagnostic Biomarkers and Host-Directed Drug Screening for Mycobacterium avium Infection: A Multi-Omics and Artificial Intelligence Study.

OBJECTIVE: The rising incidence of Mycobacterium avium (MAV) infection poses significant challenges due to diagnostic delays and refractory treatment....

AI-Enhanced Point-of-Care Diagnostics for Infectious Diseases in Resource-Limited Settings: A Scoping Review.

OBJECTIVES: To systematically map the extent and nature of research on AI-enhanced point-of-care (POC) and rapid diagnostic technologies for infectiou...