Tuberculosis

Scalable machine learning improves resistance prediction and identifies novel determinants in Mycobacterium tuberculosis

Multidrug-resistant and extensively drug-resistant Mycobacterium tuberculosis (MTB) represents a growing global health crisis, characterized by limited treatment options and high mortality rates. Rapid and accurate prediction of resistance profiles is critical to guide effective therapy and curb transmission. Whole-genome sequencing (WGS) offers promise for individualized resistance profiling, yet...

Interpretable Machine Learning Reveals Integrated Water Chemistry and Parameter-Specific Nonlinear Responses Shaping Legionella spp. and Mycobacterium spp. in Drinking Water

Traditionally, studies have explored the impacts of individual water chemistry parameters on the persistence of Mycobacterium spp. and Legionella spp. in isolation with the underlying assumption that these associations are likely monotonic in nature. Yet chemical and microbiological changes are complex, and associations are likely highly combinatorial. In this study, we use interpretable machine l...

Generative Augmentation Reveals Previously Overlooked Signals in Transcriptomic Datasets

Identifying robust gene expression signatures from transcriptomic studies with small sample sizes remains one of the most persistent challenges in com...

GS-DOT: Gaussian splatting-based image reconstruction for diffuse optical tomography

This work presents GS-DOT, a novel image reconstruction framework based on Gaussian Splatting (GS) for diffuse optical tomography (DOT). Inspired by G...

Tuberculosis in households with infectious cases in Kampala city: Harnessing health data science for new insights on an ancient disease with persistent, unresolved problems (DS-IAFRICA TB) study protocol

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...

TB-Bench: A Systematic Benchmark of Machine Learning and Deep Learning Methods for Second-Line TB Drug Resistance Prediction

Drug-resistant tuberculosis (TB), characterized by prolonged treatment regimens and suboptimal treatment outcomes, remains a major obstacle to global ...

ADD for Multi-Bit Image Watermarking

As generative models enable rapid creation of high-fidelity images, societal concerns about misinformation and authenticity have intensified. A promis...

Weight Group-wise Post-Training Quantization for Medical Foundation Model

Foundation models have achieved remarkable results in medical image analysis. However, its large network architecture and high computational complexit...

Cosine-Normalized Attention for Hyperspectral Image Classification

Transformer-based methods have improved hyperspectral image classification (HSIC) by modeling long-range spatial-spectral dependencies; however, their...

A Deployable Explainable Deep Learning System for Tuberculosis Detection from Chest X-Rays in Resource-Constrained High-Burden Settings

Abstract Objectives: To develop and evaluate a deployable deep learning system with Gradient-weighted Class Activation Mapping (Grad-CAM) for tubercul...

Federated Learning Performance Depends on Site Variation in Global HIV Data Consortia

Digital health technologies, including machine learning (ML), are transforming infectious disease management, however ML models for HIV care have been...

Spectral and non-spectral EEG measures in the prediction of working memory task performance and psychopathology

Working memory (WM) supports the temporary maintenance of goal-relevant information and is disrupted across many neuropsychiatric disorders. We examin...

BVSIMC: Bayesian Variable Selection-Guided Inductive Matrix Completion for Improved and Interpretable Drug Discovery

Recent advances in drug discovery have demonstrated that incorporating side information (e.g., chemical properties about drugs and genomic information...

A Retrospective Multi-Source Clinical Validation of Lenek Intelligent Radiology Assistant: An Artificial Intelligence-Based Chest Radiograph Screening and Triage System for High-Burden Pulmonary and Cardiac Conditions in India

Background: A critical radiologist shortage exists in India, leading to delayed chest radiograph (CXR) interpretation. This leads to disease progressi...

Fleming: An AI Agent for Antibiotic Discovery in Mycobacterium Tuberculosis

Antibiotic development is challenged by high costs and failure rates. Artificial intelligence (AI) holds promise to overcome these challenges by predi...

Cough activity detection for automatic tuberculosis screening

The automatic identification of cough segments in audio through the determination of start and end points is pivotal to building scalable screening to...

Federated Modality-specific Encoders and Partially Personalized Fusion Decoder for Multimodal Brain Tumor Segmentation

Most existing federated learning (FL) methods for medical image analysis only considered intramodal heterogeneity, limiting their applicability to mul...

Multiomic Spatial Imaging Assay (MSIA) -- A High-plex In Situ Detection Method for mRNAs, Proteins, and Protein-Protein Interactions using Manual And Semi-Automated Workflows

We report Multiomics Spatial Image Analysis (MSIA), a suite of technologies that include streamlined manual and semi-automated workflows to image 100s...

GFPL: Generative Federated Prototype Learning for Resource-Constrained and Data-Imbalanced Vision Task

Federated learning (FL) facilitates the secure utilization of decentralized images, advancing applications in medical image recognition and autonomous...

Data-Driven Hybrid Model of SARIMA-CNNAR For Tuberculosis Incidence Time Series Analysis in Nepal

Abstract Background Tuberculosis (TB) remains a major public health challenge in Nepal, with incidence rates substantially higher than global estimate...