AIMC Topic: Tuberculosis

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

Revista peruana de medicina experimental y salud publica
Tuberculosis remains an urgent issue on the urban health agenda, especially in low- and middle-income countries. There is a need to develop and implement innovative and effective solutions in the tuberculosis diagnostic process. In this article, We d...

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

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The introduction of deep learning techniques for the computer-aided detection scheme has shed a light for real incorporation into the clinical workflow. In this work, we focus on the effect of attention in deep neural networks on the classification o...

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

Chaos (Woodbury, N.Y.)
The main objective of this research is to investigate a new fractional mathematical model involving a nonsingular derivative operator to discuss the clinical implications of diabetes and tuberculosis coexistence. The new model involves two distinct p...

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

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The use of ImageNet pre-trained networks is becoming widespread in the medical imaging community. It enables training on small datasets, commonly available in medical imaging tasks. The recent emergence of a large Chest X-ray dataset opened the possi...

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

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Automatic cough detection is key to tracking the condition of patients suffering from tuberculosis. We evaluate various acoustic features for performing cough detection using deep architectures. As most previous studies have adopted features designed...

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

Current computer-aided drug design
Tuberculosis, malaria, dengue, chikungunya, leishmaniasis etc. are a large group of neglected tropical diseases that prevail in tropical and subtropical countries, affecting one billion people every year. Minimal funding and grants for research on th...

Cheminformatics Based Machine Learning Approaches for Assessing Glycolytic Pathway Antagonists of Mycobacterium tuberculosis.

Combinatorial chemistry & high throughput screening
BACKGROUND: Tuberculosis is the second leading cause of death from an infectious disease worldwide after HIV, thus reasoning the expeditions in antituberculosis research. The rising number of cases of infection by resistant forms of M. tuberculosis h...

Artificial Neural Network Analysis of Pharmacokinetic and Toxicity Properties of Lead Molecules for Dengue Fever, Tuberculosis and Malaria.

Current computer-aided drug design
Poor pharmacokinetic and toxicity profiles are major reasons for the low rate of advancing lead drug candidates into efficacy studies. The In-silico prediction of primary pharmacokinetic and toxicity properties in the drug discovery and development p...