Tuberculosis

Metaplasticity-Enabled Graphene Quantum Dot Devices for Mitigating Catastrophic Forgetting in Artificial Neural Networks.

The limitations of deep neural networks in continuous learning stem from oversimplifying the complexities of biological neural circuits, often neglecting the dynamic balance between memory stability and learning plasticity. In this study, artificial synaptic devices enhanced with graphene quantum dots (GQDs) that exhibit metaplasticity is introduced, a higher-order form of synaptic plasticity that...

Machine learning-based prediction of antibiotic resistance in Mycobacterium tuberculosis clinical isolates from Uganda.

BACKGROUND: Efforts toward tuberculosis management and control are challenged by the emergence of Mycobacterium tuberculosis (MTB) resistance to existing anti-TB drugs. This study aimed to explore the potential of machine learning algorithms in predicting drug resistance of four anti-TB drugs (rifampicin, isoniazid, streptomycin, and ethambutol) in MTB using whole-genome sequence and clinical data...

Identification of diagnostic biomarkers and molecular subtype analysis associated with m6A in Tuberculosis immunopathology using machine learning.

Tuberculosis (TB), ranking just below COVID-19 in global mortality, is a highly complex infectious disease involving intricate immunological molecules...

CNN-O-ELMNet: Optimized Lightweight and Generalized Model for Lung Disease Classification and Severity Assessment.

The high burden of lung diseases on healthcare necessitates effective detection methods. Current Computer-aided design (CAD) systems are limited by th...

Rapid diagnosis of latent and active pulmonary tuberculosis by autofluorescence spectroscopy of blood plasma combined with artificial neural network algorithm.

The existing clinical diagnostic methods of pulmonary tuberculosis (TB) usually have some of the following limitations, such as time-consuming, invasi...

Integrated machine learning and physics-based methods assisted de novo design of Fatty Acyl-CoA synthase inhibitors.

BACKGROUND: Tuberculosis is an infectious disease that has become endemic worldwide. The causative bacteria (Mtb) is targeted via several exciting dr...

Attention-based multi-residual network for lung segmentation in diseased lungs with custom data augmentation.

Lung disease analysis in chest X-rays (CXR) using deep learning presents significant challenges due to the wide variation in lung appearance caused by...

Analysis and prediction of infectious diseases based on spatial visualization and machine learning.

Infectious diseases are a global public health problem that poses a threat to human society. Since the 1970s, constantly mutated new infectious viruse...

Small Molecule Inhibitors of Topoisomerase I Identified by Machine Learning and In Vitro Assays.

Tuberculosis (TB) caused by is a leading infectious cause of death globally. The treatment of patients becomes much more difficult for the increasing...

A comprehensive study on tuberculosis prediction models: Integrating machine learning into epidemiological analysis.

Tuberculosis (TB), the second leading infectious killer globally, claimed the lives of 1.3 million individuals in 2022, after COVID-19, surpassing the...

Development and Validation of Deep Learning-Based Infectivity Prediction in Pulmonary Tuberculosis Through Chest Radiography: Retrospective Study.

BACKGROUND: Pulmonary tuberculosis (PTB) poses a global health challenge owing to the time-intensive nature of traditional diagnostic tests such as sm...

Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches.

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public health problem, resulting in > 1 million deaths each y...

Evaluating Advanced Machine Learning Models for Histopathological Diagnosis of Hansen Disease.

INTRODUCTION: Leprosy is a neglected infectious disease caused by Mycobacterium leprae and Mycobacterium lepromatosis and remains a public health chal...

Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review.

OBJECTIVE: To conduct a systematic review of the computer vision applications that detect, diagnose, or analyse tuberculosis (TB) pathology or bacilli...

Artificial intelligence-aided colonoscopic differential diagnosis between Crohn's disease and gastrointestinal tuberculosis.

BACKGROUND AND AIM: Differentiating between Crohn's disease (CD) and gastrointestinal tuberculosis (GITB) is challenging. We aimed to evaluate the cli...

Predicting Treatment Outcomes in Patients with Drug-Resistant Tuberculosis and Human Immunodeficiency Virus Coinfection, Using Supervised Machine Learning Algorithm.

Drug-resistant tuberculosis (DR-TB) and HIV coinfection present a conundrum to public health globally and the achievement of the global END TB strateg...

Machine learning algorithms to predict treatment success for patients with pulmonary tuberculosis.

Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by the Mycobacterium TB bacteria, continues to pose a...

A smartphone-integrated deep learning strategy-assisted rapid detection system for monitoring dual-modal immunochromatographic assay.

This study focuses on the integration of a custom-built and optimally trained YOLO v5 model into a smartphone app developed with Java language. A dual...

Combining bioinformatics and machine learning to identify diagnostic biomarkers of TB associated with immune cell infiltration.

OBJECTIVE: The asymptomatic nature of tuberculosis (TB) during its latent phase, combined with limitations in current diagnostic methods, makes accura...

Carbon dot unravels accumulation of triterpenoid in Evolvulus alsinoides hairy roots culture by stimulating growth, redox reactions and ANN machine learning model prediction of metabolic stress response.

Evolvulus alsinoides, a therapeutically valuable shrub can provide consistent supply of secondary metabolites (SM) with pharmaceutical significance. N...