Pulmonology

Tuberculosis

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

1,845 articles
Stay Ahead - Weekly Tuberculosis research updates
Subscribe
Browse Specialties
Showing 295-315 of 1,845 articles
Predicting antimicrobial resistance using conserved genes.

A growing number of studies are using machine learning models to accurately predict antimicrobial re...

Machine Learning-Based Differentiation of Nontuberculous Mycobacteria Lung Disease and Pulmonary Tuberculosis Using CT Images.

An increasing number of patients infected with nontuberculous mycobacteria (NTM) are observed worldw...

Machine-assisted interpretation of auramine stains substantially increases through-put and sensitivity of microscopic tuberculosis diagnosis.

Of all bacterial infectious diseases, infection by Mycobacterium tuberculosis poses one of the highe...

Computer-Aided System for the Detection of Multicategory Pulmonary Tuberculosis in Radiographs.

The early screening and diagnosis of tuberculosis plays an important role in the control and treatme...

Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning.

Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distribut...

Deep Learning Driven GC-MS Library Search and Its Application for Metabolomics.

Preliminary compound identification and peak annotation in gas chromatography-mass spectrometry is u...

Evaluation of magnesium oxide and zinc oxide nanoparticles against multi-drug-resistance Mycobacterium tuberculosis.

OBJECTIVE: The current study has evaluated the MICs and MBCs of ZnONPs, MgONPs, and MgONPs-ZnONPs ag...

Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based ...

Truncated inception net: COVID-19 outbreak screening using chest X-rays.

Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in a ...

A machine learning-based framework for Predicting Treatment Failure in tuberculosis: A case study of six countries.

Tuberculosis is ranked as the 2nd deadliest disease in the world and is responsible for ten million ...

COVID-19: The role of artificial intelligence in empowering the healthcare sector and enhancing social distancing measures during a pandemic.

Indiscriminatory in its spread, COVID-19 has engulfed communities from all social backgrounds throug...

Forecasting tuberculosis using diabetes-related google trends data.

Online activity-based data can be used to aid infectious disease forecasting. Our aim was to exploit...

A biochemically-interpretable machine learning classifier for microbial GWAS.

Current machine learning classifiers have successfully been applied to whole-genome sequencing data ...

Use of Machine Learning with Temporal Photoluminescence Signals from CdTe Quantum Dots for Temperature Measurement in Microfluidic Devices.

Because of the vital role of temperature in many biological processes studied in microfluidic device...

Artificial Intelligence and Machine learning based prediction of resistant and susceptible mutations in Mycobacterium tuberculosis.

Tuberculosis (TB), an infectious disease caused by Mycobacterium tuberculosis (M.tb), causes highest...

A Novel Low-Bit Quantization Strategy for Compressing Deep Neural Networks.

The increase in sophistication of neural network models in recent years has exponentially expanded m...

Effective metric learning with co-occurrence embedding for collaborative recommendations.

In recommender systems, matrix factorization and its variants have grown up to be dominant in collab...

Memristor-Based Edge Detection for Spike Encoded Pixels.

Memristors have many uses in machine learning and neuromorphic hardware. From memory elements in dot...

Browse Specialties