Pulmonology

Tuberculosis

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

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Predicting multiple conformations via sequence clustering and AlphaFold2.

AlphaFold2 (ref. ) has revolutionized structural biology by accurately predicting single structures ...

Effect of multimodal diagnostic approach using deep learning-based automated detection algorithm for active pulmonary tuberculosis.

In this study, we developed a model to predict culture test results for pulmonary tuberculosis (PTB)...

Treating drug-resistant tuberculosis in an era of shorter regimens: Insights from rural South Africa.

BACKGROUND: Progressive interventions have recently improved programmatic outcomes in drug-resistant...

Identification and validation of a pyroptosis-related signature in identifying active tuberculosis via a deep learning algorithm.

INTRODUCTION: Active tuberculosis (ATB), instigated by Mycobacterium tuberculosis (M.tb), rises as a...

Deep learning and radiomics of longitudinal CT scans for early prediction of tuberculosis treatment outcomes.

BACKGROUND: To predict tuberculosis (TB) treatment outcomes at an early stage, prevent poor outcomes...

Batch normalization followed by merging is powerful for phenotype prediction integrating multiple heterogeneous studies.

Heterogeneity in different genomic studies compromises the performance of machine learning models in...

Localization and phenotyping of tuberculosis bacteria using a combination of deep learning and SVMs.

Successful treatment of pulmonary tuberculosis (TB) depends on early diagnosis and careful monitorin...

Research on cloud manufacturing service recommendation based on graph neural network.

There are an increasing number of manufacturing service resources appeared on the cloud manufacturin...

First fully-automated AI/ML virtual screening cascade implemented at a drug discovery centre in Africa.

Streamlined data-driven drug discovery remains challenging, especially in resource-limited settings....

3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning.

A novel multi-channel-based 3D convolutional neural network (3D-CNN) is proposed in this paper to cl...

Two-stage classification strategy for breast cancer diagnosis using ultrasound-guided diffuse optical tomography and deep learning.

SIGNIFICANCE: Ultrasound (US)-guided diffuse optical tomography (DOT) has demonstrated great potenti...

Incidental radiological findings during clinical tuberculosis screening in Lesotho and South Africa: a case series.

BACKGROUND: Chest X-ray offers high sensitivity and acceptable specificity as a tuberculosis screeni...

Using optimal transport theory to optimize a deep convolutional neural network microscopic cell counting method.

Medical image processing has become increasingly important in recent years, particularly in the fiel...

FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction.

Near-infrared diffuse optical tomography (DOT) is a promising functional modality for breast cancer ...

Imaging inside highly scattering media using hybrid deep learning and analytical algorithm.

Imaging through highly scattering media is a challenging problem with numerous applications in biome...

Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians.

Predictive artificial intelligence (AI) systems based on deep learning have been shown to achieve ex...

Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review.

BACKGROUND: Tuberculosis (TB) was the leading infectious cause of mortality globally prior to COVID-...

Digerati - A multipath parallel hybrid deep learning framework for the identification of mycobacterial PE/PPE proteins.

The genome of Mycobacterium tuberculosis contains a relatively high percentage (10%) of genes that a...

An Integrated Approach to Improve the Assay Performance of Quantum Dot-Based Lateral Flow Immunoassays by Using Silver Deposition.

Traditional quantum dot-based lateral flow immunoassay (QD-LFIA) is limited to signal loss in part b...

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