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Precision Health Database


Precision Health Database|Search|PHGKB

Last data update: Jun 04, 2023. (Total: 60074 Documents since 2012)
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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
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
Machine learning approaches in diagnosing tuberculosis through biomarkers - A systematic review.
Vimala Balakrishnan et al. Progress in biophysics and molecular biology 2023 17916-25
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)
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
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
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
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)
The role of machine learning in HIV risk prediction.
Fieggen Joshua et al. Frontiers in reproductive health 2023 41062387
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
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
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
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
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
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)
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
Computer-aided diagnostic for classifying chest X-ray images using deep ensemble learning.
Visuña Lara et al. BMC medical imaging 2022 22(1) 178
Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods.
You Shiying et al. PLOS digital health 2022 1(6)
Raman spectroscopy and machine learning-based optical probe for tuberculosis diagnosis via sputum.
Ullah Ubaid et al. Tuberculosis (Edinburgh, Scotland) 2022 136102251
The Application of Artificial Intelligence in the Diagnosis and Drug Resistance Prediction of Pulmonary Tuberculosis.
Liang Shufan et al. Frontiers in medicine 2022 9935080
Clinical application and diagnostic accuracy of artificial intelligence in colonoscopy for inflammatory bowel disease: systematic review.
Yang Linda S et al. Endoscopy international open 2022 10(7) E1004-E1013
Using Machine Learning Techniques and National Tuberculosis Surveillance Data to Predict Excess Growth in Genotyped Tuberculosis Clusters.
Althomsons Sandy P et al. American journal of epidemiology 2022
Making cough count in tuberculosis care
AJ Zimmer et al, Comm Medicine, July 6, 2022
Prediction and Diagnosis of Respiratory Disease by Combining Convolutional Neural Network and Bi-directional Long Short-Term Memory Methods.
Li Li et al. Frontiers in public health 2022 10881234
Diagnostic accuracy of a commercially-available, deep learning-based chest-Xray interpretation software for detecting culture-confirmed pulmonary tuberculosis.
Tavaziva Gamuchirai et al. International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 2022
Machine learning-based in-hospital mortality prediction of HIV/AIDS patients with Talaromyces marneffei infection in Guangxi, China.
Shi Minjuan et al. PLoS neglected tropical diseases 2022 16(5) e0010388
Artificial Intelligence Assisting the Early Detection of Active Pulmonary Tuberculosis From Chest X-Rays: A Population-Based Study.
Nijiati Mayidili et al. Frontiers in molecular biosciences 2022 9874475
TB-Net: A Tailored, Self-Attention Deep Convolutional Neural Network Design for Detection of Tuberculosis Cases From Chest X-Ray Images.
Wong Alexander et al. Frontiers in artificial intelligence 2022 5827299
Infectious diseases prevention and control using an integrated health big data system in China.
Zhou Xudong et al. BMC infectious diseases 2022 22(1) 344
A treatment recommender clinical decision support system for personalized medicine: method development and proof-of-concept for drug resistant tuberculosis.
Verboven Lennert et al. BMC medical informatics and decision making 2022 22(1) 56
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