Steven Schalekamp
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View article: Does BMI influence AI and human reader lung nodule detection in low-dose chest CT?
Does BMI influence AI and human reader lung nodule detection in low-dose chest CT? Open
Sensitivity for lung nodule detection in LDCT was not significantly different for high versus low BMI, either for AI or human reader. Compared to the human reader, AI had higher FP/scan in both BMI groups.
View article: Performance of AI to exclude normal chest radiographs to reduce radiologists’ workload
Performance of AI to exclude normal chest radiographs to reduce radiologists’ workload Open
View article: How AI should be used in radiology: assessing ambiguity and completeness of intended use statements of commercial AI products
How AI should be used in radiology: assessing ambiguity and completeness of intended use statements of commercial AI products Open
View article: Nodule detection and generation on chest X-rays: NODE21 Challenge
Nodule detection and generation on chest X-rays: NODE21 Challenge Open
Pulmonary nodules may be an early manifestation of lung cancer, the leading cause of cancer-related deaths among both men and women. Numerous studies have established that deep learning methods can yield high-performance levels in the dete…
View article: COVID-19 screening in low resource settings using artificial intelligence for chest radiographs and point-of-care blood tests
COVID-19 screening in low resource settings using artificial intelligence for chest radiographs and point-of-care blood tests Open
View article: Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans
Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans Open
Background Outside a screening program, early-stage lung cancer is generally diagnosed after the detection of incidental nodules in clinically ordered chest CT scans. Despite the advances in artificial intelligence (AI) systems for lung ca…
View article: Duration and accuracy of automated stroke CT workflow with AI-supported intracranial large vessel occlusion detection
Duration and accuracy of automated stroke CT workflow with AI-supported intracranial large vessel occlusion detection Open
View article: AI-support for the detection of intracranial large vessel occlusions: One-year prospective evaluation
AI-support for the detection of intracranial large vessel occlusions: One-year prospective evaluation Open
View article: Clinical use of artificial intelligence products for radiology in the Netherlands between 2020 and 2022
Clinical use of artificial intelligence products for radiology in the Netherlands between 2020 and 2022 Open
Objectives To map the clinical use of CE-marked artificial intelligence (AI)–based software in radiology departments in the Netherlands ( n = 69) between 2020 and 2022. Materials and methods Our AI network (one radiologist or AI representa…
View article: Invasive Fungal Disease in Patients with Myeloid Malignancies: A Retrospective Cohort Study of a Diagnostic-Driven Care Pathway Withholding Mould-Active Prophylaxis
Invasive Fungal Disease in Patients with Myeloid Malignancies: A Retrospective Cohort Study of a Diagnostic-Driven Care Pathway Withholding Mould-Active Prophylaxis Open
Objectives: Patients receiving remission induction therapy for acute myeloid leukaemia (AML) are at high risk of developing invasive fungal disease (IFD). Newer therapies with targeted antileukemic agents and the emergence of azole resista…
View article: Explainable emphysema detection on chest radiographs with deep learning
Explainable emphysema detection on chest radiographs with deep learning Open
We propose a deep learning system to automatically detect four explainable emphysema signs on frontal and lateral chest radiographs. Frontal and lateral chest radiographs from 3000 studies were retrospectively collected. Two radiologists a…
View article: Deep Learning for Lung Cancer Detection on Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists
Deep Learning for Lung Cancer Detection on Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists Open
Deep learning algorithms developed in a public competition for lung cancer detection in low-dose CT scans reached performance close to that of radiologists.Keywords: Lung, CT, Thorax, Screening, Oncology Supplemental material is …
View article: Cost-effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment
Cost-effectiveness of artificial intelligence aided vessel occlusion detection in acute stroke: an early health technology assessment Open
Background Limited evidence is available on the clinical impact of artificial intelligence (AI) in radiology. Early health technology assessment (HTA) is a methodology to assess the potential value of an innovation at an early stage. We us…
View article: Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective
Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective Open
View article: How does artificial intelligence in radiology improve efficiency and health outcomes?
How does artificial intelligence in radiology improve efficiency and health outcomes? Open
View article: Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs
Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs Open
The developed CNN achieved radiologist-level performance in detecting scaphoid bone fractures on conventional radiographs of the hand, wrist, and scaphoid.Keywords: Convolutional Neural Network (CNN), Deep Learning Algorithms, Machi…
View article: Artificial intelligence in radiology: 100 commercially available products and their scientific evidence
Artificial intelligence in radiology: 100 commercially available products and their scientific evidence Open
View article: Chest CT in the Emergency Department for Diagnosis of COVID-19 Pneumonia: Dutch Experience
Chest CT in the Emergency Department for Diagnosis of COVID-19 Pneumonia: Dutch Experience Open
Background Clinicians need to rapidly and reliably diagnose coronavirus disease 2019 (COVID-19) for proper risk stratification, isolation strategies, and treatment decisions. Purpose To assess the real-life performance of radiologist emerg…
View article: Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19
Model-based Prediction of Critical Illness in Hospitalized Patients with COVID-19 Open
Background The prognosis of hospitalized patients with severe coronavirus disease 2019 (COVID-19) is difficult to predict, and the capacity of intensive care units was a limiting factor during the peak of the pandemic and is generally depe…
View article: Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence
Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence Open
Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest infections suspected to be caused by COVID-19 using chest CT may…
View article: COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System
COVID-19 on Chest Radiographs: A Multireader Evaluation of an Artificial Intelligence System Open
Background Chest radiography may play an important role in triage for coronavirus disease 2019 (COVID-19), particularly in low-resource settings. Purpose To evaluate the performance of an artificial intelligence (AI) system for detection o…
View article: Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification
Cardiomegaly Detection on Chest Radiographs: Segmentation Versus Classification Open
In this study, we investigate the detection of cardiomegaly on frontal chest radiographs through two alternative deep-learning approaches - via anatomical segmentation and via image-level classification. We used the publicly available Ches…
View article: The Effect of Supplementary Bone-Suppressed Chest Radiographs on the Assessment of a Variety of Common Pulmonary Abnormalities
The Effect of Supplementary Bone-Suppressed Chest Radiographs on the Assessment of a Variety of Common Pulmonary Abnormalities Open
BSI does not negatively affect the interpretation of diffuse lung disease, while improving visualization of focal lesions on chest radiographs. BSI leads to overcalling of focal abnormalities in normal radiographs.
View article: Advanced processing in chest radiography: impact on observer performance
Advanced processing in chest radiography: impact on observer performance Open