Pulmonology

Tuberculosis

Latest AI and machine learning research in tuberculosis for healthcare professionals.

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Hamming Attention Distillation: Binarizing Keys and Queries for Efficient Long-Context Transformers

Pre-trained transformer models with extended context windows are notoriously expensive to run at scale, often limiting real-world deployment due to their high computational and memory requirements. In this paper, we introduce Hamming Attention Distillation (HAD), a novel framework that binarizes keys and queries in the attention mechanism to achieve significant efficiency gains. By converting ke...

Reduced-order modeling and classification of hydrodynamic pattern formation in gravure printing

Hydrodynamic pattern formation phenomena in printing and coating processes are still not fully understood. However, fundamental understanding is essential to achieve high-quality printed products and to tune printed patterns according to the needs of a specific application like printed electronics, graphical printing, or biomedical printing. The aim of the paper is to develop an automated patter...

Optimal Transport Barycenter via Nonconvex-Concave Minimax Optimization

The optimal transport barycenter (a.k.a. Wasserstein barycenter) is a fundamental notion of averaging that extends from the Euclidean space to the W...

Deep Learning-Powered Classification of Thoracic Diseases in Chest X-Rays

Chest X-rays play a pivotal role in diagnosing respiratory diseases such as pneumonia, tuberculosis, and COVID-19, which are prevalent and present u...

RL-RC-DoT: A Block-level RL agent for Task-Aware Video Compression

Video encoders optimize compression for human perception by minimizing reconstruction error under bit-rate constraints. In many modern applications ...

Enhanced Tuberculosis Bacilli Detection using Attention-Residual U-Net and Ensemble Classification

Tuberculosis (TB), caused by Mycobacterium tuberculosis, remains a critical global health issue, necessitating timely diagnosis and treatment. Curre...

Efficient and Accurate Tuberculosis Diagnosis: Attention Residual U-Net and Vision Transformer Based Detection Framework

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis, continues to be a major global health threat despite being preventabl...

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

Large-language models (LLMs) can parse vast amounts of data and generate executable code, positioning them as promising tools for the development of b...

Intra-genomic genes-to-genes correlation enables bacterial genome representation

The bacterial pan-genome consists of core genes shared by all members of a taxonomy and accessory genes found in only a subset. The correlation among ...

Accurate and robust classification of Mycobacterium bovis-infected cattle using peripheral blood RNA-seq data

The zoonotic bacterium, Mycobacterium bovis, causes bovine tuberculosis (bTB) and is closely related to Mycobacterium tuberculosis, the primary cause ...

Evolutionary Reasoning Does Not Arise in Standard Usage of Protein Language Models

Protein language models (PLMs) are often assumed to capture evolutionary information by training on large protein sequence datasets. Yet it remains un...

Predicting pyrazinamide resistance in Mycobacterium tuberculosis using a graph convolutional network

Pyrazinamide is an important first-line antibiotic for treating tuberculosis and resistance is primarily caused by mutations in the pncA gene. Traditi...

Artificial Intelligence-enabled Histological Analysis in Preclinical Respiratory Disease Models: A Scoping Review

Histological analysis is a cornerstone of preclinical respiratory disease research, enabling assessment of pathology, therapeutic effects, and mechani...

GenVS-TBDB: A Target-Aware AI-Generated and Virtual-Screened Small-Molecule Library for Tuberculosis Drug Discovery

Tuberculosis (TB) remains a leading global health threat, with over 10 million new cases and 1.25 million deaths reported in 2023. Current TB therapie...

Efficient Classification of Pulmonary Pneumonia and Tuberculosis Alongside Normal and Non-X-ray Images with Minimal Resources and Maximum Accuracy

Pneumonia, primarily caused by Streptococcus pneumoniae, and tuberculosis (TB), caused by Mycobacterium tuberculosis, continue to present significant ...

SYSTEMS AND NETWORK BIOLOGY ANALYSIS COMBINED WITH MACHINE LEARNING IDENTIFIES KEY IMMUNE RESPONSE PROFILES AND POTENTIAL CORRELATES OF PROTECTION FOR THE M72/AS01E TUBERCULOSIS VACCINE

Tuberculosis claims around 1.5 million lives annually. The M72/AS01E vaccine candidate is an innovative effort demonstrating a 50% reduction in the in...

A micro-ChromaDot array with AI integration for the detection of multiple biomarkers in a small portable device

With the rapid growth of digital healthcare, diagnosis, prognosis, and monitoring of chronic and acute diseases at home are increasingly in demand. In...

Plasma proteomics for novel biomarker discovery in childhood tuberculosis

Failure to rapidly diagnose tuberculosis disease (TB) and initiate treatment is a driving factor of TB as a leading cause of death in children. Curren...

Tuberculosis disease severity assessment using clinical variables and radiology enabled by artificial intelligence

Radiology can define tuberculosis (TB) severity and may guide duration of treatment, however the optimal radiological metric to use and which clinical...

A mechanistic neural network model predicts both potency and toxicity of antimicrobial combination therapies

Antimicrobial resistance poses a major global threat due to the diminishing efficacy of current treatments and limited new therapies. Combination ther...

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