Deep learning and radiomics of longitudinal CT scans for early prediction of tuberculosis treatment outcomes

Deep learning-based pulmonary tuberculosis automated detection on chest radiography: large-scale independent testing

(2022) Wen Zhou et al.   Quantitative Imaging in Medicine and Surgery

Radiologist observations of computed tomography (CT) images predict treatment outcome in TB Portals, a real-world database of tuberculosis (TB) cases

(2021) Gabriel Rosenfeld et al.   PLoS One

World Health Organization treatment outcome definitions for tuberculosis: 2021 update

(2021) Nguyen Nhat Linh et al.   EUROPEAN RESPIRATORY JOURNAL

A fully automatic artificial intelligence–based CT image analysis system for accurate detection, diagnosis, and quantitative severity evaluation of pulmonary tuberculosis

(2021) Chenggong Yan et al.   EUROPEAN RADIOLOGY

Performance of Qure.ai automatic classifiers against a large annotated database of patients with diverse forms of tuberculosis

(2020) Eric Engle et al.   PLoS One

Quantitative 18F-FDG PET-CT scan characteristics correlate with tuberculosis treatment response

(2020) Stephanus T. Malherbe et al.   EJNMMI Research

Clinically Applicable AI System for Accurate Diagnosis, Quantitative Measurements, and Prognosis of COVID-19 Pneumonia Using Computed Tomography

(2020) Kang Zhang et al.   CELL

Value of 18F-FDG PET/CT radiomic features to distinguish solitary lung adenocarcinoma from tuberculosis

(2020) Yujing Hu et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Radiomics nomogram for preoperative differentiation of lung tuberculoma from adenocarcinoma in solitary pulmonary solid nodule

(2020) Bao Feng et al.   EUROPEAN JOURNAL OF RADIOLOGY

Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging

(2019) Yiwen Xu et al.   CLINICAL CANCER RESEARCH

Artificial Intelligence, Radiology, and Tuberculosis: A Review

(2019) Sagar Kulkarni et al.   ACADEMIC RADIOLOGY

Risk factors for the occurrence of multidrug-resistant tuberculosis among patients undergoing multidrug-resistant tuberculosis treatment in East Shoa, Ethiopia

(2018) Fanta Desissa et al.   BMC PUBLIC HEALTH

Predicting treatment outcome of drug-susceptible tuberculosis patients using machine-learning models

(2018) Owais A. Hussain et al.   Informatics for Health & Social Care

Prediction of Multidrug-Resistant TB from CT Pulmonary Images Based on Deep Learning Techniques

(2018) Xiaohong W. Gao et al.   MOLECULAR PHARMACEUTICS

Current treatment of multidrug resistant tuberculosis in Ethiopia: an aggregated and individual patients’ data analysis for outcome and effectiveness of the current regimens

(2018) Setegn Eshetie et al.   BMC INFECTIOUS DISEASES

Feature selection and prediction of treatment failure in tuberculosis

(2018) Christopher Martin Sauer et al.   PLoS One

Detecting drug-resistant tuberculosis in chest radiographs

(2018) Stefan Jaeger et al.   International Journal of Computer Assisted Radiology and Surgery

Evaluation of factors associated with failure of tuberculosis treatment under DOTS in northern Islamic Republic of Iran

(2016) Khalil Ali Mohammadzadeh et al.   EASTERN MEDITERRANEAN HEALTH JOURNAL

Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study

(2015) Timothy M Walker et al.   LANCET INFECTIOUS DISEASES

PET/CT imaging correlates with treatment outcome in patients with multidrug-resistant tuberculosis

(2014) R. Y. Chen et al.   Science Translational Medicine

Rapid molecular TB diagnosis: evidence, policy making and global implementation of Xpert MTB/RIF

(2012) Karin Weyer et al.   EUROPEAN RESPIRATORY JOURNAL