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Sputum

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Sputum Neutrophil Gelatinase-Associated Lipocalin as a Biomarker in Asthma-COPD Overlap.

The Journal of the Association of Physicians of India
BACKGROUND: Asthma COPD overlap (ACO) is a consensus-based phenotype having characteristics of both COPD and asthma. Distinguishing ACO from other diseases is even more important as it is related to low health-related quality of life, augmented exace...

Machine-assisted interpretation of auramine stains substantially increases through-put and sensitivity of microscopic tuberculosis diagnosis.

Tuberculosis (Edinburgh, Scotland)
Of all bacterial infectious diseases, infection by Mycobacterium tuberculosis poses one of the highest morbidity and mortality burdens on humans throughout the world. Due to its speed and cost-efficiency, manual microscopy of auramine-stained sputum ...

On-Site Detection of SARS-CoV-2 Antigen by Deep Learning-Based Surface-Enhanced Raman Spectroscopy and Its Biochemical Foundations.

Analytical chemistry
A rapid, on-site, and accurate SARS-CoV-2 detection method is crucial for the prevention and control of the COVID-19 epidemic. However, such an ideal screening technology has not yet been developed for the diagnosis of SARS-CoV-2. Here, we have devel...

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

PloS one
Despite advancements in detection and treatment, tuberculosis (TB), an infectious illness caused by the Mycobacterium TB bacteria, continues to pose a serious threat to world health. The TB diagnosis phase includes a patient's medical history, physic...

Retrospective validation of MetaSystems' deep-learning-based digital microscopy platform with assistance compared to manual fluorescence microscopy for detection of mycobacteria.

Journal of clinical microbiology
UNLABELLED: This study aimed to validate Metasystems' automated acid-fast bacilli (AFB) smear microscopy scanning and deep-learning-based image analysis module (Neon Metafer) with assistance on respiratory and pleural samples, compared to conventiona...

Artificial intelligence-based radiographic extent analysis to predict tuberculosis treatment outcomes: a multicenter cohort study.

Scientific reports
Predicting outcomes in pulmonary tuberculosis is challenging despite effective treatments. This study aimed to identify factors influencing treatment success and culture conversion, focusing on artificial intelligence (AI)-based chest X-ray analysis ...

Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection.

Medical & biological engineering & computing
Deep learning is a transformative force in the medical field and it has made significant progress as a pivotal alternative to conventional manual testing methods. Detection of Tubercle Bacilli in sputum samples is faced with the problems of complex b...

ResGloTBNet: An interpretable deep residual network with global long-range dependency for tuberculosis screening of sputum smear microscopy images.

Medical engineering & physics
Tuberculosis is a high-mortality infectious disease. Manual sputum smear microscopy is a common and effective method for screening tuberculosis. However, it is time-consuming, labor-intensive, and has low sensitivity. In this study, we propose ResGlo...