Tuberculosis

Improved screening for pulmonary Kaposi sarcoma in a low-resource setting.

OBJECTIVE: The lung is commonly involved in advanced Kaposi sarcoma (KS) but diagnosis of pulmonary KS in low-resource settings is difficult. Clinical assessments were evaluated to improve screening for pulmonary KS in a low-resource setting. METHODS: A longitudinal cohort of Africans with HIV-associated KS in the Parirenyatwa Hospital KS clinic, Harare, Zimbabwe, was followed from 2016 to 2018. A...

An Integrated Deep Learning Framework Leveraging NASNet and Vision Transformer with MixProcessing for Accurate and Precise Diagnosis of Lung Diseases.

Lung diseases such as pneumonia, tuberculosis, COVID-19, and lung cancer remain significant global health challenges that demand rapid and accurate diagnosis to improve patient outcomes. This study proposes NASNet-ViT, a novel deep learning framework that integrates the powerful convolutional feature extraction of NASNet with the global attention mechanisms of the Vision Transformer (ViT). To enha...

Multidimensional analysis of clinical pharmacist intervention impact on hospital length of stay in pulmonary tuberculosis: a random forest-driven retrospective study.

Construction of a diagnostic model for tuberculosis based on long non-coding RNA.

BACKGROUND: The World Health Organization encourages the development of novel diagnostic tools based on 'non-sputum' samples to meet global goals for ...

Predicting the diabetic foot in patients with type 2 diabetes mellitus based on machine learning.

BACKGROUND: Diabetic foot (DF) is a severe complication of type 2 diabetes mellitus (T2DM), contributing to significant morbidity and healthcare costs...

Artificial Intelligence in Pleural Diseases: Current Applications and Next Steps.

Pleural diseases pose a significant burden on healthcare systems due to diagnostic challenges and high costs. Artificial intelligence (AI) has the pot...

Future Prospects for Using Clinical Phenotypes in Tuberculosis Precision Medicine-An Approach for Clinical Management.

Developing shorter treatment regimens for tuberculosis requires careful characterization of the clinical phenotype, which is defined by patient charac...

Plasma proteomics biomarkers for predicting anti-tuberculosis drug-induced liver injury: A comprehensive assessment.

AIMS: This study aims to identify predictive plasma protein biomarkers for anti-tuberculosis drug-induced liver injury (ATB-DILI) and develop machine ...

Rapid, non-invasive diagnosis of tuberculosis using desorption separation ionization mass spectrometry (DSI-MS) and urinary carbonyl metabolite fingerprints.

Tuberculosis (TB) remains a leading global infectious disease that demands rapid, non-invasive diagnostic solutions. Here, we present a rapid urine-ba...

Epidemiologic trajectories and burden of multidrug-resistant tuberculosis (MDR-TB) mortality across South Asia: An analysis of Global Burden of Disease data (1990-2023) with machine learning forecasting to 2050.

BACKGROUND: Multidrug-resistant tuberculosis (MDR-TB) remains a major public health challenge in South Asia, which bears a disproportionate global bur...

Nanopore Analysis of Malto-oligosaccharides from Amylose, Amylopectin, and Cyclodextrin Hydrolysates.

Malto-oligosaccharides, structurally diverse glucose polymers comprising 2-10 monosaccharide units, play vital roles in food science, pharmaceuticals,...

Harnessing artificial intelligence and machine learning to accelerate structure-based drug discovery for tuberculosis.

Continual low-rank scaled dot-product attention.

Transformers are widely used for their ability to capture data relations in sequence processing, with great success for a wide range of static tasks. ...

HERC5, IFI6, IFIT3, and OASL as potential diagnostic biomarkers for systemic lupus erythematosus: an integrated bioinformatics, machine learning and clinical validation.

OBJECTIVES: Systemic lupus erythematosus (SLE) is a life-threatening autoimmune disorder causing multi-organ damage. Current diagnostic methods are hi...

Improving Genotype Imputation in High-Dimensional Pharmacogenomics Using Multiple Imputation: Evaluation with Machine Learning Approaches.

Multiple imputation is well-established for handling missing data, yet its use in high-dimensional genetic datasets remains limited. Using pharmacokin...

HeptaTB Dx: a diagnostic model leveraging cuproptosis-ferroptosis crosstalk for distinguishing latent from active tuberculosis.

UNLABELLED: Distinguishing latent tuberculosis infection (LTBI) from active tuberculosis (ATB) remains challenging. The roles of cuproptosis-ferroptos...

Machine learning-driven graphene quantum dot fluorescence array for rapid heavy metal ions detection and identification.

The growing threat of heavy metal ions (HMIs) to human health and the ecological environment has underscored the need for advanced sensor technologies...

Advances in antituberculosis drug-induced liver injury: Molecular mechanisms, genetic insights, and emerging animal-free prediction models.

Approximately 10 million tuberculosis patients worldwide require drug therapies annually. However, prolonged use of tuberculocidal drugs in combinatio...

Nationwide longitudinal evaluation of a machine learning approach for enhanced interpretation of Xpert MTB/RIF ultra rifampicin-resistance results in low bacterial load tuberculosis specimens.

BACKGROUND: The World Health Organization (WHO) has identified tuberculosis (TB) as the leading cause of death from a single infectious agent. False-p...

Vit-Ensemble: Probabilistic voting based ensemble of Vision Transformers for tuberculosis detection using radiographs.

Tuberculosis (TB) detection from chest X-ray (CXR) images remains a critical challenge in global healthcare. This study introduces Vit-Ensemble, a nov...