Pulmonology

Tuberculosis

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

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Digging Deeper to Save the Old Anti-tuberculosis Target: D-Alanine-D-Alanine Ligase With a Novel Inhibitor, IMB-0283.

The emergence of drug-resistant (Mtb) has hampered treatments for tuberculosis, which consequently ...

Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India.

In general, chest radiographs (CXR) have high sensitivity and moderate specificity for active pulmon...

Comparison of the predictive outcomes for anti-tuberculosis drug-induced hepatotoxicity by different machine learning techniques.

BACKGROUND: The study compared the predictive outcomes of artificial neural network, support vector ...

Characterization of the complete chloroplast genome of (Cupressaceae), an herb to treat lumbar tuberculosis in China.

belongs to the family Cupressaceae that the branches and leaves is an important Traditional Chinese...

Artificial intelligence applications for thoracic imaging.

Artificial intelligence is a hot topic in medical imaging. The development of deep learning methods ...

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making.

Identifying and understanding the risk factors for endemic bovine tuberculosis (TB) in cattle herds ...

Chemometric challenges in development of paper-based analytical devices: Optimization and image processing.

Although microfluidic paper-based analytical devices (μPADs) get a lot of attention in the scientifi...

Artificial Intelligence, Radiology, and Tuberculosis: A Review.

Tuberculosis is a leading cause of death from infectious disease worldwide, and is an epidemic in ma...

A genetic programming-based approach to identify potential inhibitors of serine protease of .

We applied genetic programming approaches to understand the impact of descriptors on inhibitory eff...

ATBdiscrimination: An in Silico Tool for Identification of Active Tuberculosis Disease Based on Routine Blood Test and T-SPOT.TB Detection Results.

Tuberculosis remains one of the deadliest infectious diseases worldwide. Only 5-15% of people infect...

Automated Counting of Cancer Cells by Ensembling Deep Features.

High-content and high-throughput digital microscopes have generated large image sets in biological e...

Deep Learning Diffuse Optical Tomography.

Diffuse optical tomography (DOT) has been investigated as an alternative imaging modality for breast...

SecProMTB: Support Vector Machine-Based Classifier for Secretory Proteins Using Imbalanced Data Sets Applied to Mycobacterium tuberculosis.

Secretory proteins of Mycobacterium tuberculosis have created more concern, given their dominant imm...

Creating the Black Box: A Primer on Convolutional Neural Network Use in Image Interpretation.

Convolutional neural networks have been shown to demonstrate high diagnostic performance in radiolog...

An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.

BACKGROUND AND OBJECTIVE: Chest X-ray (CXR) is one of the most used imaging techniques for detection...

Compact and Computationally Efficient Representation of Deep Neural Networks.

At the core of any inference procedure, deep neural networks are dot product operations, which are t...

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