Tuberculosis

Rapid Endoscopic Diagnosis of Benign Ulcerative Colorectal Diseases With an Artificial Intelligence Contextual Framework.

BACKGROUND & AIMS: Benign ulcerative colorectal diseases (UCDs) such as ulcerative colitis, Crohn's ...

Multi-modal deep learning methods for classification of chest diseases using different medical imaging and cough sounds.

Chest disease refers to a wide range of conditions affecting the lungs, such as COVID-19, lung cance...

From CNN to Transformer: A Review of Medical Image Segmentation Models.

Medical image segmentation is an important step in medical image analysis, especially as a crucial p...

Deep Learning Radiomics Analysis of CT Imaging for Differentiating Between Crohn's Disease and Intestinal Tuberculosis.

This study aimed to develop and evaluate a CT-based deep learning radiomics model for differentiatin...

PulmoNet: a novel deep learning based pulmonary diseases detection model.

Pulmonary diseases are various pathological conditions that affect respiratory tissues and organs, m...

Clinical utilization of artificial intelligence in predicting therapeutic efficacy in pulmonary tuberculosis.

Traditional methods for monitoring pulmonary tuberculosis (PTB) treatment efficacy lack sensitivity,...

Machine learning assisted methods for the identification of low toxicity inhibitors of Enoyl-Acyl Carrier Protein Reductase (InhA).

Tuberculosis (TB) is one of the life-threatening infectious diseases with prehistoric origins and oc...

Application of artificial intelligence in diagnosis of pulmonary tuberculosis.

TB-DROP: deep learning-based drug resistance prediction of Mycobacterium tuberculosis utilizing whole genome mutations.

The most widely practiced strategy for constructing the deep learning (DL) prediction model for drug...

Deep learning model to differentiate Crohn's disease from intestinal tuberculosis using histopathological whole slide images from intestinal specimens.

Crohn's disease (CD) and intestinal tuberculosis (ITB) share similar histopathological characteristi...

Explainable deep-neural-network supported scheme for tuberculosis detection from chest radiographs.

Chest radiographs are examined in typical clinical settings by competent physicians for tuberculosis...

Lung-DT: An AI-Powered Digital Twin Framework for Thoracic Health Monitoring and Diagnosis.

The integration of artificial intelligence (AI) with Digital Twins (DTs) has emerged as a promising ...

A bipolar intuitionistic fuzzy decision-making model for selection of effective diagnosis method of tuberculosis.

OBJECTIVES: Tuberculosis (TB) is a contagious illness caused by Mycobacterium tuberculosis. The init...

Artificial intelligence-based screening for amblyopia and its risk factors: comparison with four classic stereovision tests.

INTRODUCTION: The development of costs-effective and sensitive screening solutions to prevent amblyo...

Early user perspectives on using computer-aided detection software for interpreting chest X-ray images to enhance access and quality of care for persons with tuberculosis.

Despite 30 years as a public health emergency, tuberculosis (TB) remains one of the world's deadlies...

Investigating Novel IspE Inhibitors of the MEP Pathway in Mycobacterium.

In a recent effort to mitigate harm from human pathogens, many biosynthetic pathways have been exten...

MRI advances in the imaging diagnosis of tuberculous meningitis: opportunities and innovations.

Tuberculous meningitis (TBM) is not only one of the most fatal forms of tuberculosis, but also a maj...

A Vision for the Future of Astrochemistry in the Interstellar Medium by 2050.

By 2050, many, but not nearly all, unattributed astronomical spectral features will be conclusively ...

Strengthening the Diagnosis of Drug-Resistant Tuberculosis Using NGS-Based Approaches and Bioinformatics Pipelines for Data Analysis in India.

In India, drug-resistant tuberculosis (DR-TB) is a major public health issue and a significant chall...

Distinguishing infectivity in patients with pulmonary tuberculosis using deep learning.

INTRODUCTION: This study aimed to develop and assess a deep-learning model based on CT images for di...

Identifying the Interaction Between Tuberculosis and SARS-CoV-2 Infections via Bioinformatics Analysis and Machine Learning.

The number of patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 is st...