Evidence (Publications & White Papers)

Implementation costs and cost-effectiveness of ultraportable chest X-ray with artificial intelligence in active case finding for tuberculosis in Nigeria

A systematic review and meta-analysis of artificial intelligence software for tuberculosis diagnosis using chest X-ray imaging

Prevalence of Xpert MTB/RIF Ultra Trace Call Results and Associated Risk Factors During Active Tuberculosis Case Finding in Viet Nam: A Programmatic Evaluation

Investigating low uptake of tuberculin skin testing when integrated with active case-finding for TB

Diagnostic Accuracy of Artificial Intelligence-Based Chest X-Ray reading for screening of Tuberculosis

Qure.ai increases TB detection, while saving costs, shows evaluation in India

Type and physical intensity of occupations at pulmonary TB diagnosis

Diagnostic Performance of a Computer-aided System for Tuberculosis Screening in Two Philippine Cities

Mobile phone-based computer-aided chest X-ray detects TB as well as trained radiologists

Diagnostic Accuracy of Chest X-ray Computer-Aided Detection Software for Detection of Prevalent and Incident Tuberculosis in Household Contacts

AI Improves Lung Nodule Detection in Multi-Center Study

Detection of other pathologies when utilising computer-assisted digital solutions for TB screening

Normal and Abnormal Chest X-Ray Classification at Visa Screening Centers in UAE

Quantifying sputum production success during community-based screening for TB

Musculoskeletal fracture detection: artificial intelligence and machine learning-based diagnostic advantages and pitfalls (Texas Tech University Health Sciences Center School of Medicine)

Detecting tuberculosis with AI-powered active case finding in Vietnam

Advances in Deep Learning for Tuberculosis Screening using Chest X-rays: The Last 5 Years Review

A retrospective audit of an artificial intelligence software for the detection of intracranial haemorrhage used by a teleradiology company in the United Kingdom

Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage

Accuracy of an artificial intelligence-enabled diagnostic assistance device in recognising normal chest radiographs: A service evaluation

Enhancing Stroke Care with AI at Baptist Christian Hospital

Evidence at 2024 World Conference on Lung Cancer cites chest X-ray AI’s potential to detect lung nodules early

Computer-aided detection of tuberculosis from chest radiographs in a tuberculosis prevalence survey in South Africa: external validation and modelled impacts of commercially available artificial intelligence software

Comparing the Output of an Artificial Intelligence Algorithm in Detecting Radiological Signs of Pulmonary Tuberculosis in Digital Chest X-Rays and Their Smartphone-Captured Photos of X-Ray Films: Retrospective Study

Independent evaluation of the accuracy of 5 artificial intelligence software for detecting lung nodules on chest X-rays

Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries

Early Detection of Heart Failure with Autonomous AI-Based Model Using Chest Radiographs: A Multicenter Study

Artificial Intelligence-based automated CT brain interpretation to accelerate treatment for acute stroke in rural India: An interrupted time series study

Validation of a commercially available CAD-system for lung nodule detection and characterization using CT-scans

An Effective Health System Approach to End TB: Implementing the Double X Strategy in Vietnam

The utility of artificial intelligence in identifying radiological evidence of lung cancer and pulmonary tuberculosis in a high-burden tuberculosis setting

Evaluation of an artificial intelligence-based software device for detection of intracranial haemorrhage in teleradiology practice

Revolutionizing Healthcare: Qure.AI's Innovations in Medical Diagnosis and Treatment

Comparing deep learning models for tuberculosis detection: A retrospective study of digital vs. analog chest radiographs

Correlating Age and Hematoma Volume with Extent of Midline Shift in Acute Subdural Hematoma Patients: Validation of an Artificial Intelligence Tool for Volumetric Analysis

Assessing the effectiveness of artificial intelligence (AI) in prioritising CT head interpretation: study protocol for a stepped-wedge cluster randomised trial (ACCEPT-AI)

Benefits of Artificial Intelligence versus Human- Reader in Chest X-ray Screening for Tuberculosis in the Philippines

Deploying artificial intelligence software in an NHS trust: a how-to guide for clinicians

Early user perspectives on using computer-aided detection software for interpreting chest X-ray images to enhance access and quality of care for persons with tuberculosis

11 clinical trials that will shape medicine in 2024

Implementing a chest X-ray artificial intelligence tool to enhance tuberculosis screening in India: Lessons learned

Using Artificial Intelligence to Stratify Normal versus Abnormal Chest X-rays: External Validation of a Deep Learning Algorithm at East Kent Hospitals University NHS Foundation Trust

Computer-Aided Detection for Chest Radiography to Improve the Quality of Tuberculosis Diagnosis in Vietnam's District Health Facilities: An Implementation Study

Comparing tuberculosis symptom screening to chest X-ray with artificial intelligence in an active case finding campaign in Northeast Nigeria

Comparative Assessment of Chest X-ray Interpretations by AI Model and Radiologist Vs Pulmonologist in Predicting the Clinical Status of Covid-19 Pneumonia Patients

Qure.ai receives 510(k) FDA clearance for its Chest X-ray solution for Pneumothorax and Pleural Effusion, Elevating ICU and ER Care Pathways

The diagnostic value of chest X-ray scanning by the help of Artificial Intelligence in Heart Failure (ART-IN-HF)

FDA Clears Qure.ai's qXR-CTR Chest X-ray Solution as a Potential Indicator for Identifying Heart Failure Risk

Benchmarking the diagnostic test accuracy of certified AI products for screening pulmonary tuberculosis in digital chest radiographs: Preliminary evidence from a rapid review and meta-analysis

Comparative Evaluation of Digital and Analog Chest Radiographs to Identify Tuberculosis using Deep Learning Model

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

The rise of artificial intelligence reading of chest X-rays for enhanced TB diagnosis and elimination

Teleradiology and technology innovations in radiology: status in India and its role in increasing access to primary health care

Artificial intelligence-reported chest X-ray findings of culture-confirmed pulmonary tuberculosis in people with and without diabetes

Early user experience and lessons learned using ultra-portable digital X-ray with computer-aided detection (DXR-CAD) products: A qualitative study from the perspective of healthcare providers

Mind the Clot: Automated LVO Detection on CTA Using Deep Learning

Diagnostic Accuracy of the Artificial Intelligence Methods in Medical Imaging for Pulmonary Tuberculosis: A Systematic Review and Meta-Analysis

Economic analysis of different throughput scenarios and implementation strategies of computer-aided detection software as a screening and triage test for pulmonary TB

Performance of a Chest Radiography AI Algorithm for Detection of Missed or Mislabeled Findings: A Multicenter Study

Role of an Automated Deep Learning Algorithm for Reliable Screening of Abnormality in Chest Radiographs: A Prospective Multicenter Quality Improvement Study

Accuracy of automated intracerebral hemorrhage volume measurement on non-contrast computed tomography: a Swedish Stroke Register cohort study

Frequency of Missed Findings on Chest Radiographs (CXRs) in an International, Multicenter Study: Application of AI to Reduce Missed Findings

The Performance of Computer-Aided Detection Digital Chest X-ray Reading Technologies for Triage of Active Tuberculosis Among Persons With a History of Previous Tuberculosis

Evolution of Machine Learning in Tuberculosis Diagnosis: A Review of Deep Learning-Based Medical Applications

Deep-ASPECTS: A Segmentation-Assisted Model for Stroke Severity Measurement

Utility of Xpert MTB/RIF Ultra and digital chest radiography for the diagnosis and treatment of TB in people living with HIV: a randomised controlled trial (XACT-TB)

Identifying malignant nodules on chest X-rays: A validation study of radiologist versus artificial intelligence diagnostic accuracy

Comparing different versions of computer-aided detection products when reading chest X-rays for tuberculosis

The Early diagnostic value of chest X-ray scanning by the help of Artificial Intelligence in Heart Failure (ART-IN-HF): The First Outcomes

Using artificial intelligence to risk stratify COVID-19 patients based on chest X-ray findings.

Using artificial intelligence to risk stratify COVID19 patients based on chest X-ray findings

Evaluation of chest X-Ray with automated interpretation algorithms for mass tuberculosis screening in prisons

Triage of Persons With Tuberculosis Symptoms Using Artificial Intelligence–Based Chest Radiograph Interpretation: A Cost-Effectiveness Analysis

Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis

Early Evaluation of an Ultra-Portable X-ray System for Tuberculosis Active Case Finding

Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms

Pattern of abnormalities amongst chest X-rays of adults undergoing computer-assisted digital chest X-ray screening for tuberculosis in Peri-Urban Blantyre, Malawi: A cross-sectional study

Deep Learning-Based Software Tools for Tuberculosis Detection in Chest X-Ray Images

Application of artificial intelligence in digital chest radiography reading for pulmonary tuberculosis screening

Artificial intelligence matches subjective severity assessment of pneumonia for prediction of patient outcome and need for mechanical ventilation – a cohort study

Automated Lateral Ventricular and Cranial Vault Volume Measurements in 13,851 Subjects Utilizing Deep Learning Algorithms

A new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers

Deep Learning-Based A.I. Software for Chest X-Ray Analysis to Detect Microbiologically-Confirmed Tuberculosis: A Prospective Study of Diagnostic Accuracy

Chest x-ray analysis with deep learning-based software as a triage test for pulmonary tuberculosis – a prospective study of diagnostic accuracy for culture-confirmed disease

Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients – analysis of 697 Italian patients

A Systematic Review of Medical Costs Associated with Heart Failure in the USA (2014–2020)

Artificial Intelligence Solutions for Analysis of X-ray Images

Comparison of Chest Radiograph Interpretations by Artificial Intelligence vs Radiologists in the diagnosis of pulmonary TB

Can artificial intelligence (AI) be used to accurately detect tuberculosis (TB) from chest x-ray? A multiplatform evaluation of five AI products used for TB screening in a high TB-burden setting

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

Deep learning, computer-aided radiography reading for tuberculosis – A diagnostic accuracy study from a tertiary hospital in India

Segmentation and Measurement of Ventricular and Cranial Vault Volumes in 15,223 Subjects Using Artificial Intelligence

Clinical Context Improves the Performance of AI Models for Cranial Fracture Detection

AUC and Enriched Datasets are Not Good Enough Anymore: Presenting an Alternative Metric to Evaluate Radiology AI Models

Using artificial intelligence to read chest radiographs for tuberculosis detection – A multi-site evaluation of the diagnostic accuracy of three deep learning systems

Automated classification of X-rays as normal/Abnormal using a high sensitivity deep learning algorithm

Automated Detection and Localization of Pneumocephalus in Head CT scan

Automated Detection of Midline Shift and Mass Effect from Head CT Scans using Deep Learning

Prospective evaluation of a deep learning algorithm deployed in an urban imaging centre to notify clinicians of head CT scans with critical abnormalities

Deep Learning for Infarct Detection and Localization from Head CT Scans

Validation of Deep Learning Algorithms for Detection of Critical Findings in Head CT Scans

Deep learning algorithms for detection of critical findings in head CT scans – A retrospective study

Deep learning in chest radiography: Detection of findings and presence of change

Can Artificial Intelligence Reliably Report Chest X-Rays? Radiologist Validation of an Algorithm trained on 1.2 Million X-Rays

Machine Learning Methods Improve Prognostication, Identify Clinically Distinct Phenotypes, and Detect Heterogeneity in Response to Therapy in a Large Cohort of Heart Failure Patients

Development and Validation of Deep Learning Algorithms for Detection of Critical Findings in Head CT Scans

Efficacy of deep learning for screening pulmonary tuberculosis

Identifying pulmonary consolidation in Chest X Rays using deep learning

Automated detection of intra- and extra-axial haemorrhages on CT brain images using deep neural networks

Clinical validation of a deep learning algorithm for quantification of the idiopathic pulmonary fibrosis pattern

Automated detection and localisation of skull fractures from CT scans using deep learning

Variation in practice patterns and outcomes across United Network for Organ Sharing allocation regions

Deep Neural Networks to Identify and Localize Intracerebral Hemorrhage and Midline Shift in CT Scans of Brain

Generating Heatmaps to Visualize the Evidence of Deep Learning Based Diagnosis of Chest X-Rays

2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation

Improving Boundary Classification for Brain Tumor Segmentation and Longitudinal Disease Progression

A Deep-Learning Based Approach for Ischemic Stroke Lesion Outcome Prediction