Tuberculosis

Temporal Knowledge Discovery in Drug-Resistant Tuberculosis: A Decade-Long Machine Learning Analysis From Egyptian Clinical Data.

BACKGROUND: Advanced predictive tools are required due to the worldwide persistence of tuberculosis (TB) and the growing threat of multidrug-resistant tuberculosis (MDR-TB). The rate and precision of traditional diagnostic techniques frequently experience delays. This study uses machine learning (ML) to identify clinical and longitudinal treatment-history risk factors for drug-resistant tuberculos...

Reverse AIEE/ACQ Engineering in a Carbon Dot-Quantum Dot Ratiometric Nanosensor: Machine-Learning-Driven Quantitative and Recognition Detection of Biogenic Amines for Food Freshness Monitoring.

Simultaneous profiling of biogenic amines, including spermine, putrescine, cadaverine, histamine, and tyramine, is crucial for assessing food freshness, tracking spoilage progression, and preventing associated foodborne illnesses and adverse health effects. Herein, we report a chemically unmodified dual-emissive nanosensor constructed by noncovalent integration of green carbon dots (G-CDs) and nea...

Enhancing lung diseases recognition through CNN-RNN methodologies.

Diagnostics of respiratory disorders greatly benefit from medical imaging, especially X-ray imaging, which offers important information about the anat...

DIGITAL SOLUTIONS FOR TUBERCULOSIS SURVEILLANCE AND CONTROL IN PRIMARY HEALTH CARE: A SCOPING REVIEW.

Digital solutions are essential for eliminating tuberculosis as a public health problem. They can be applied across all stages of patient care, health...

Federated Learning Framework for Privacy-Preserving Explainable AI-Driven Clinical Decision-Making.

The application of artificial intelligence (AI) in clinical diagnostics has shown substantial potential; however, conventional centralized learning fr...

Imaging Modalities in Tuberculosis.

Tuberculosis (TB) remains a major global health challenge, with increasing prevalence of multidrug-resistant and extrapulmonary forms complicating dia...

Dual-Peptide Nanoplatform: Mesoporous Silica Nanoparticles Functionalized With a Cell-Penetrating Peptide and Loaded With Rationally Designed Antimicrobial Peptides for Tuberculosis Therapy.

Tuberculosis remains a major infectious disease worldwide and demands new therapeutic approaches capable of targeting intracellular Mycobacterium tube...

A machine learning-based prediction model for treatment efficacy in smear and/or chest X-ray positive tuberculosis patients.

PTBD: a machine learning-based non-invasive diagnostic model for pulmonary tuberculosis using large-scale blood transcriptomes.

BACKGROUND: Accurate and rapid diagnosis is essential for controlling pulmonary tuberculosis (PTB) by enabling timely intervention and reducing diseas...

Diagnostic accuracy of AI-assisted chest radiographs in tuberculosis screening: A Ghanaian clinical study.

BACKGROUND: Tuberculosis remains a major global health challenge, particularly in resource-limited settings where access to expert radiological interp...

Genome-wide detection of human 5' UTR variants that impact protein translation.

The 5' untranslated region (5' UTR) of messenger RNAs (mRNAs) plays a central role in regulating protein synthesis initiation, particularly through th...

Machine learning algorithms for identifying tuberculous pericardial effusion: insights from a retrospective study in Vietnam.

BACKGROUND: Tuberculous pericardial effusion (TPE) presents significant diagnostic challenges due to its nonspecific clinical presentation and similar...

Challenges and Opportunities for Improved Tuberculosis and HIV Prevention in South America.

Tuberculosis (TB) and human immunodeficiency virus (HIV) cause significant morbidity and mortality in South America. Despite the advances in active ca...

Identification of tuberculosis transmission hotspots in urban China using surveillance data: a machine learning approach based on genomic and spatial analysis.

Predicting progression of Mycobacterium avium complex pulmonary disease with treatment using explainable artificial intelligence techniques.

OBJECTIVES: The incidence of nontuberculous mycobacterial pulmonary disease (NTM-PD) is rising; however, only certain patients experience disease prog...

Machine learning prediction of tuberculosis mortality: a comparative analysis of random survival forest and cox regression models.

Value of Endobronchial Ultrasound-Derived Radiomics in Differentiating Pulmonary Sarcoidosis from Mediastinal Lymph Node Tuberculosis.

INTRODUCTION: To explore the feasibility of an ultrasound radiomics machine learning model based on endobronchial ultrasound (EBUS) for differentiatin...

Bone tuberculosis: molecular pathogenesis, diagnostic advances, therapeutic challenges, and emerging strategies for effective management.

Targeting metabolism to combat anticancer and antibacterial drug resistance.

Drug resistance is a major challenge in cancer and infectious diseases, requiring innovative solutions. Recent research suggests that bacteria and can...

Leveraging machine learning for accurate forecasting of pulmonary tuberculosis epidemics in a coastal city in China.

BACKGROUND: While pulmonary tuberculosis (PTB) remains a leading notifiable cause of death in China, city-level monthly forecasts with sufficient reso...