Tuberculosis

Benchmarking large language models for cell-free RNA diagnostic biomarker discovery.

Large language models can synthesize biomedical knowledge, parse vast amounts of data, and generate code, positioning them as promising tools for biomarker discovery from high-throughput omics data. Here, we benchmark six models from OpenAI, Anthropic, and Google on plasma cell-free RNA datasets spanning three clinical cohorts: Kawasaki disease versus multisystem inflammatory syndrome in children,...

Benchmarking deep learning architectures for MALDI-TOF mass spectrometry in infectious disease diagnostics and vector-borne disease surveillance.

Emerging global health threats, from antimicrobial resistance to vector-borne diseases, require scalable diagnostic solutions. Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry has revolutionized microbial diagnostics but remains underutilized in public health due to algorithmic challenges in interpreting and generalizing complex spectra. Here, we present a s...

Artificial intelligence-enabled histological analysis in pre-clinical respiratory disease models: a scoping review.

Histological analysis is a cornerstone of pre-clinical respiratory disease research. It enables assessment of pathology, therapeutic effects, and mech...

Deep learning approach for probabilistic pulmonary function estimation from chest X-ray and peak expiratory flow rate.

BACKGROUND: Spirometry remains the gold standard for assessing pulmonary function. Deep learning models have demonstrated potential for estimating mea...

A novel deep learning network for small bowel ulcerative lesion detection and differential diagnosis on double-balloon endoscopy images.

Differentiating small bowel ulcerative diseases (SBUDs) on double-balloon endoscopy (DBE) is challenging. We aimed to develop an artificial intelligen...

Machine learning versus clinical scoring systems for predicting poor wound healing after posterior surgery for thoracolumbar tuberculosis.

OBJECTIVE: Postoperative poor wound healing (PWH) is a significant complication following posterior surgery for thoracolumbar tuberculosis, leading to...

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...

Network analysis of pairwise relative tuberculosis transmission probabilities in Lima, Peru.

Identifying transmission events is important in understanding infectious disease dynamics. Such events are typically unobservable, particularly in res...

Artificial intelligence in paediatric chest imaging: applications, challenges, and future directions.

BACKGROUND: Paediatric chest imaging is central to diagnosing respiratory and cardiopulmonary disease, particularly in low- and middle-income countrie...

Characteristics of Plausible Source Cases Responsible for Recent Mycobacterium tuberculosis Transmission, United States, 2018-2022.

Tuberculosis (TB) outbreaks in the United States can cause substantial illness. Using surveillance and genotyping data, we applied a plausible source-...

UV spectroscopy associated with machine learning as a complementary tool for the diagnosis of Ehrlichia canis in dogs.

Canine ehrlichiosis, caused by Ehrlichia canis, is a tick-borne disease with a global distribution that significantly affects the clinical and epidemi...

Development and validation of a serum microRNA biomarker panel for bovine Johne's disease.

Johne's disease (JD) is a chronic wasting disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). For decades, JD manage...

AdPrST:An Adversarial Graph Deep Learning Pre-clustering Framework for Deciphering Spatiotemporal Structures in Spatially Resolved Transcriptomics.

Spatially Resolved Transcriptomics (SRT) has revolutionized our understanding of gene expression within tissue microenvironments, yet accurately decip...

A Disorder-Aware Computational Framework to Identify Structurally Tractable Targets in Proliferative Vitreoretinopathy.

OBJECTIVE: Proliferative vitreoretinopathy (PVR) remains a major cause of failure after rhegmatogenous retinal detachment repair and lacks effective p...

Microplastics and the Endocrine-Metabolic Interface: Novel Diagnostic Tools Targeting Thyroid-Adipose Axis.

Microplastics (MPs) have been identified as major environmental contaminants that can affect organisms directly and act as carriers of particles and c...

Quantum Dot Encoding for In-Solution Single-Molecule Biomarker Counting in Metastatic Prostate Cancer.

Digital assays are in wide development for biomarker quantification at the single-molecule level, but the common use of surface pull-down steps limits...

Advances in quantum dot-based fluorescent biosensors for enzyme detection: mechanistic insights and applications in disease.

It is imperative to develop precise detection tools for enzymes, as key biomarkers in disease pathogenesis, to fuel progress in clinical diagnostics a...

Machine learning-assisted carbon dot sensing for iron speciation in Auricularia auricula soaking solutions under various processing conditions.

Accurate iron speciation in Auricularia auricula soaking solution is essential for evaluating nutritional quality, as bioavailability depends on its v...

Computational fluid dynamics and machine learning modeling of drug delivery by hydroxypropyl methylcellulose.

This study integrates computational fluid dynamics (CFD) simulations with machine learning (ML) models to develop a framework for predicting drug rele...

Blood Transcriptomic Signatures Distinguish Mycobacterium avium Complex Pulmonary Disease from Colonization: A Multicenter Cohort Study.

AbstractPulmonary infections caused by nontuberculous mycobacteria (NTM), particularly Mycobacterium avium complex (MAC), are increasingly recognized ...