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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
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Last data update: Mar 28, 2024
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Explainable machine learning for early predicting treatment failure risk among patients with TB-diabetes comorbidity.
An-Zhou Peng et al. Sci Rep 2024 14(1) 6814
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Integrative analysis of multimodal patient data identifies personalized predictors of tuberculosis treatment prognosis.
Awanti Sambarey et al. iScience 2024 27(2) 109025
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Distinguishing infectivity in patients with pulmonary tuberculosis using deep learning.
Yi Gao et al. Front Public Health 2023 111247141
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High-Throughput Phenotypic Screening and Machine Learning Methods Enabled the Selection of Broad-Spectrum Low-Toxicity Antitrypanosomatidic Agents.
Pasquale Linciano et al. J Med Chem 2023
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Development and validation of a diagnostic model to differentiate spinal tuberculosis from pyogenic spondylitis by combining multiple machine learning algorithms.
Chengqian Huang et al. Biomol Biomed 2023
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Current challenges and potential solutions to the use of digital health technologies in evidence generation: a narrative review.
Hassan Mumtaz et al. Front Digit Health 2023 51203945
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Comparison of logistic regression with regularized machine learning methods for the prediction of tuberculosis disease in people living with HIV: cross-sectional hospital- based study in Kisumu County, Kenya.
James Orwa et al. Res Sq 2023
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Deep Learning Classification of Tuberculosis Chest X-rays.
Kartik K Goswami et al. Cureus 2023 15(7) e41583
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Diagnostic accuracy of three computer-aided detection systems for detecting pulmonary tuberculosis on chest radiography when used for screening: Analysis of an international, multicenter migrants screening study.
Sifrash Meseret Gelaw et al. PLOS Glob Public Health 2023 3(7) e0000402
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Machine and Deep Learning for Tuberculosis Detection on Chest X-Rays: Systematic Literature Review.
Seng Hansun et al. J Med Internet Res 2023 25e43154
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A machine learning approach to explore individual risk factors for tuberculosis treatment non-adherence in Mukono district.
Haron W Gichuhi et al. PLOS Glob Public Health 2023 3(7) e0001466
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Chest Radiography of Tuberculosis: Determination of Activity using Deep Learning Algorithm.
Ye Ra Choi et al. Tuberc Respir Dis (Seoul) 2023
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A prospective observational multicentric clinical trial to evaluate microscopic examination of acid-fast bacilli in sputum by artificial intelligence-based microscopy system.
Prashant Gupta et al. J Investig Med 2023 10815589231171402
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Machine learning approaches in diagnosing tuberculosis through biomarkers - A systematic review.
Vimala Balakrishnan et al. Progress in biophysics and molecular biology 2023 17916-25
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Machine Learning Prediction Model of Tuberculosis Incidence Based on Meteorological Factors and Air Pollutants.
Na Tang et al. International journal of environmental research and public health 2023 20(5)
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Mycobacterial cavity on chest computed tomography: clinical implications and deep learning-based automatic detection with quantification.
Ieun Yoon et al. Quantitative imaging in medicine and surgery 2023 13(2) 747-762
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Identification of Active Pulmonary Tuberculosis Among Patients With Positive Interferon-Gamma Release Assay Results: Value of a Deep Learning-based Computer-aided Detection System in Different Scenarios of Implementation.
Jongsoo Park et al. Journal of thoracic imaging 2023
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Deep learning classification of active tuberculosis lung zones wise manifestations using chest X-rays: a multi label approach.
Devasia James et al. Scientific reports 2023 13(1) 887
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Diagnostic Accuracy of the Artificial Intelligence Methods in Medical Imaging for Pulmonary Tuberculosis: A Systematic Review and Meta-Analysis.
Zhan Yuejuan et al. Journal of clinical medicine 2023 12(1)
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The role of machine learning in HIV risk prediction.
Fieggen Joshua et al. Frontiers in reproductive health 2023 41062387
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Multicentre external validation of a commercial artificial intelligence software to analyse chest radiographs in health screening environments with low disease prevalence.
Kim Cherry et al. European radiology 2023
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Deep learning based CT images automatic analysis model for active/non-active pulmonary tuberculosis differential diagnosis.
Nijiati Mayidili et al. Frontiers in molecular biosciences 2022 91086047
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Use of big data on the social determinants of TB to find the "missing millions".
Biermann O et al. The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease 2022 26(12) 1194-1196
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Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review.
Maturana Carles Rubio et al. Frontiers in microbiology 2022 131006659
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Development and application of survey-based artificial intelligence for clinical decision support in managing infectious diseases: A pilot study on a hospital in central Vietnam.
Kim Kwanghyun et al. Frontiers in public health 2022 101023098
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Evaluation of an AI-Based TB AFB Smear Screening System for Laboratory Diagnosis on Routine Practice.
Fu Hsiao-Ting et al. Sensors (Basel, Switzerland) 2022 22(21)
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Meta-Analysis and Data Mining-Based Study on the Expression Characteristics of Inflammatory Factors and Causes of Recurrence in Spinal Tuberculosis.
Wang Jun et al. Computational and mathematical methods in medicine 2022 20228246510
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Computer-aided diagnostic for classifying chest X-ray images using deep ensemble learning.
Visuña Lara et al. BMC medical imaging 2022 22(1) 178
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Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods.
You Shiying et al. PLOS digital health 2022 1(6)
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Raman spectroscopy and machine learning-based optical probe for tuberculosis diagnosis via sputum.
Ullah Ubaid et al. Tuberculosis (Edinburgh, Scotland) 2022 136102251
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Page last reviewed:
Feb 1, 2024
Page last updated:
Mar 28, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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