Pulmonology

Tuberculosis

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

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Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN.

Effective and timely antibiotic treatment depends on accurate and rapid in silico antimicrobial-resi...

Differentiation of intestinal tuberculosis and Crohn's disease through an explainable machine learning method.

Differentiation between Crohn's disease and intestinal tuberculosis is difficult but crucial for med...

Deep Modular Bilinear Attention Network for Visual Question Answering.

VQA (Visual Question Answering) is a multi-model task. Given a picture and a question related to the...

E-TBNet: Light Deep Neural Network for Automatic Detection of Tuberculosis with X-ray DR Imaging.

Currently, the tuberculosis (TB) detection model based on chest X-ray images has the problem of exce...

Mycobacterium abscessus drug discovery using machine learning.

The prevalence of infections by nontuberculous mycobacteria is increasing, having surpassed tubercul...

The Compact Support Neural Network.

Neural networks are popular and useful in many fields, but they have the problem of giving high conf...

TBNet: a context-aware graph network for tuberculosis diagnosis.

Tuberculosis (TB) is an infectious bacterial disease. It can affect the human lungs, brain, bones, a...

Magnetic Resonance Imaging Images under Deep Learning in the Identification of Tuberculosis and Pneumonia.

This work aimed to explore the application value of deep learning-based magnetic resonance imaging (...

Deep learning aided quantitative analysis of anti-tuberculosis fixed-dose combinatorial formulation by terahertz spectroscopy.

Anti-tuberculosis fixed-dose combinatorial formulation (FDCs) is an effective drug for the treatment...

Ensemble of EfficientNets for the Diagnosis of Tuberculosis.

Tuberculosis (TB) remains a life-threatening disease and is one of the leading causes of mortality i...

Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis.

There have been few independent evaluations of computer-aided detection (CAD) software for tuberculo...

Rapid detection of using magnetic nanobead-based immunoseparation and quantum dot-based immunofluorescence.

In recent years, the scale of population exposure and food poisoning caused by () has shown a signi...

Development of a Machine learning image segmentation-based algorithm for the determination of the adequacy of Gram-stained sputum smear images.

BACKGROUND: Machine learning (ML) prepares and trains a model through supervised or unsupervised lea...

Diagnostic Value of Deep Learning-Based CT Feature for Severe Pulmonary Infection.

The study aimed to explore the diagnostic value of computed tomography (CT) images based on cavity c...

A Novel and Robust Approach to Detect Tuberculosis Using Transfer Learning.

Deep learning has emerged as a promising technique for a variety of elements of infectious disease m...

Remaining Useful Life Estimation of Aircraft Engines Using a Joint Deep Learning Model Based on TCNN and Transformer.

The remaining useful life estimation is a key technology in prognostics and health management (PHM) ...

An accurate artificial intelligence system for the detection of pulmonary and extra pulmonary Tuberculosis.

Tuberculosis (TB) is the greatest irresistible illness in humans, caused by microbes Mycobacterium T...

A Novel COVID-19 Diagnosis Support System Using the Stacking Approach and Transfer Learning Technique on Chest X-Ray Images.

COVID-19 is an infectious disease-causing flu-like respiratory problem with various symptoms such as...

Machine learning in the prediction of medical inpatient length of stay.

Length of stay (LOS) estimates are important for patients, doctors and hospital administrators. Howe...

DenResCov-19: A deep transfer learning network for robust automatic classification of COVID-19, pneumonia, and tuberculosis from X-rays.

The global pandemic of coronavirus disease 2019 (COVID-19) is continuing to have a significant effec...

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