Pulmonology

Tuberculosis

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

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Deep learning assistance for tuberculosis diagnosis with chest radiography in low-resource settings.

Tuberculosis (TB) is a major health issue with high mortality rates worldwide. Recently, tremendous ...

[Artificial intelligence and innovation to optimize the tuberculosis diagnostic process].

Tuberculosis remains an urgent issue on the urban health agenda, especially in low- and middle-incom...

A Study on Tuberculosis Classification in Chest X-ray Using Deep Residual Attention Networks.

The introduction of deep learning techniques for the computer-aided detection scheme has shed a ligh...

Artificial intelligence and the future of global health.

Concurrent advances in information technology infrastructure and mobile computing power in many low ...

A Deep Learning Approach to Antibiotic Discovery.

Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new...

Convolutional neural network-based approach to estimate bulk optical properties in diffuse optical tomography.

Deep learning has been actively investigated for various applications such as image classification, ...

Developing and verifying automatic detection of active pulmonary tuberculosis from multi-slice spiral CT images based on deep learning.

OBJECTIVE: Diagnosis of tuberculosis (TB) in multi-slice spiral computed tomography (CT) images is a...

Recent Advancement in Predicting Subcellular Localization of Mycobacterial Protein with Machine Learning Methods.

Mycobacterium tuberculosis (MTB) can cause the terrible tuberculosis (TB), which is reported as one ...

iATP: A Sequence Based Method for Identifying Anti-tubercular Peptides.

BACKGROUND: Tuberculosis is one of the biggest threats to human health. Recent studies have demonstr...

A new and efficient numerical method for the fractional modeling and optimal control of diabetes and tuberculosis co-existence.

The main objective of this research is to investigate a new fractional mathematical model involving ...

Development and Validation of a Deep Learning-based Automatic Detection Algorithm for Active Pulmonary Tuberculosis on Chest Radiographs.

BACKGROUND: Detection of active pulmonary tuberculosis on chest radiographs (CRs) is critical for th...

Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset.

The use of ImageNet pre-trained networks is becoming widespread in the medical imaging community. It...

A Comparative Study of Features for Acoustic Cough Detection Using Deep Architectures.

Automatic cough detection is key to tracking the condition of patients suffering from tuberculosis. ...

Simultaneous Determination of Isoniazid, Pyrazinamide and Rifampin in Human Plasma by High-performance Liquid Chromatography and UV Detection.

Therapeutic Drug Monitoring (TDM) of first-line anti-tuberculosis (TB) drugs is a decisive tool, all...

Precision immunoprofiling to reveal diagnostic signatures for latent tuberculosis infection and reactivation risk stratification.

Latent tuberculosis infection (LTBI) is estimated in nearly one quarter of the world's population, a...

Computational Approaches as Rational Decision Support Systems for Discovering Next-Generation Antitubercular Agents: Mini-Review.

Tuberculosis, malaria, dengue, chikungunya, leishmaniasis etc. are a large group of neglected tropic...

Back-propagation neural network-based reconstruction algorithm for diffuse optical tomography.

Diffuse optical tomography (DOT) is a promising noninvasive imaging modality and is capable of provi...

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