AIMC Topic: Tuberculosis

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An Imbalanced Learning based MDR-TB Early Warning System.

Journal of medical systems
As a man-made disease, multidrug-resistant tuberculosis (MDR-TB) is mainly caused by improper treatment programs and poor patient supervision, most of which could be prevented. According to the daily treatment and inspection records of tuberculosis (...

A tuberculosis ontology for host systems biology.

Tuberculosis (Edinburgh, Scotland)
A major hurdle facing tuberculosis (TB) investigators who want to utilize a rapidly growing body of data from both systems biology approaches and omics technologies is the lack of a standard vocabulary for data annotation and reporting. Lacking a mea...

RAIRS2 a new expert system for diagnosing tuberculosis with real-world tournament selection mechanism inside artificial immune recognition system.

Medical & biological engineering & computing
Tuberculosis is a major global health problem that has been ranked as the second leading cause of death from an infectious disease worldwide, after the human immunodeficiency virus. Diagnosis based on cultured specimens is the reference standard; how...

AI-powered digital stethoscopes: A new opportunity in tuberculosis screening?

Med (New York, N.Y.)
Tuberculosis screening faces challenges of under-detection, costly approaches, and inequitable access. AI-enabled digital stethoscopes have demonstrated promising accuracy and feasibility for detecting lung and cardiovascular abnormalities, with prom...

Machine Learning-based Prediction of Active Tuberculosis in People With HIV Using Clinical Data.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
BACKGROUND: Coinfections of Mycobacterium tuberculosis (MTB) and human immunodeficiency virus (HIV) impose a substantial global health burden. Patients with MTB infection face a heightened risk of progression to incident active TB, which preventive t...

Streamlining tuberculosis detection with foundation model-based weakly supervised transformer.

Computers in biology and medicine
Tuberculosis (TB) remains a major global health challenge, particularly in low- and middle-income countries. Traditional microscopy-based diagnostics are labor-intensive and error-prone, while automated deep learning models often require detailed exp...

Artificial intelligence for TB education and counselling: a modified Delphi consensus.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
BACKGROUNDOptimal TB care and control requires improved health education and effective patient counselling. Effective counselling is a lengthy process that requires addressing all questions related to TB transmission, risk, the di...

Use of a convolutional neural network for direct detection of acid-fast bacilli from clinical specimens.

Microbiology spectrum
Mycobacteria, including (MTB) and non-tuberculosis mycobacteria (NTM), are important causes of infectious disease and cause significant mortality and morbidity globally. Fast detection is extremely important to reduce transmission and mortality asso...

Multiomics and Machine Learning Identify Immunometabolic Biomarkers for Active Tuberculosis Diagnosis Against Nontuberculous Mycobacteria and Latent Tuberculosis Infection.

Journal of proteome research
This study utilized multiomics combined with a comprehensive machine learning-based predictive modeling approach to identify, validate, and prioritize circulating immunometabolic biomarkers in distinguishing tuberculosis (TB) from nontuberculous myco...