Errol Colak
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View article: 43 NATURAL LANGUAGE PROCESSING MODEL-BASED SOLUTION FOR LABELING BRAIN METASTASIS IN RADIOLOGY REPORTS
43 NATURAL LANGUAGE PROCESSING MODEL-BASED SOLUTION FOR LABELING BRAIN METASTASIS IN RADIOLOGY REPORTS Open
Brain Cancer Canada Travel Award Recipient Brain metastases (BM) far exceed primary CNS tumours and constitute the majority workload for neuro-oncology care providers. Canadian Cancer Registry captures ~2800 BM identified at the primary ca…
View article: High performance with fewer labels using semi-weakly supervised learning for pulmonary embolism diagnosis
High performance with fewer labels using semi-weakly supervised learning for pulmonary embolism diagnosis Open
View article: The use of a convolutional neural network to automate radiologic scoring of computed tomography of paranasal sinuses
The use of a convolutional neural network to automate radiologic scoring of computed tomography of paranasal sinuses Open
View article: Underreliance Harms Human-AI Collaboration More Than Overreliance in Medical Imaging
Underreliance Harms Human-AI Collaboration More Than Overreliance in Medical Imaging Open
Importance: The use of artificial intelligence (AI) to support clinicians in diagnostic decision-making holds significant potential; however, evidence regarding its clinical utility remains mixed. In many cases, the interaction between hea…
View article: Artificial intelligence for abdominopelvic trauma imaging: trends, gaps, and future directions
Artificial intelligence for abdominopelvic trauma imaging: trends, gaps, and future directions Open
View article: X-ray modalities in the era of artificial intelligence: overview of self-supervised learning approach
X-ray modalities in the era of artificial intelligence: overview of self-supervised learning approach Open
Self-supervised learning enables the creation of algorithms that outperform supervised pre-training methods in numerous computer vision tasks. This paper provides a comprehensive overview of self-supervised learning applications across var…
View article: Signatures of chronic pain in multiple sclerosis: a machine learning approach to investigate trigeminal neuralgia
Signatures of chronic pain in multiple sclerosis: a machine learning approach to investigate trigeminal neuralgia Open
Chronic pain is a pervasive, disabling, and understudied feature of multiple sclerosis (MS), a progressive demyelinating and neurodegenerative disease. Current focus on motor components of MS disability combined with difficulties assessing…
View article: The Brain Tumor Segmentation (BraTS) Challenge 2023: <i>Brain MR Image Synthesis for Tumor Segmentation (BraSyn)</i>.
The Brain Tumor Segmentation (BraTS) Challenge 2023: <i>Brain MR Image Synthesis for Tumor Segmentation (BraSyn)</i>. Open
Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input magnetic resonance imaging (MRI) modalities: T1-weighted ima…
View article: Underreliance Harms Human-AI Collaboration More Than Overreliance in Medical Imaging
Underreliance Harms Human-AI Collaboration More Than Overreliance in Medical Imaging Open
Importance: The use of artificial intelligence (AI) to support clinicians in diagnostic decision-making holds significant potential; however, evidence regarding its clinical utility remains mixed. In many cases, the interaction between hea…
View article: The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset
The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset Open
The RSNA Abdominal Traumatic Injury CT (ie, RATIC) dataset contains 4274 abdominal CT studies with annotations related to traumatic injuries and is available at https://www.kaggle.com/competitions/rsna-2023-abdominal-trauma-detection and h…
View article: Assessing the Performance of Models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a Level I Trauma Center
Assessing the Performance of Models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a Level I Trauma Center Open
Winning machine learning models from the RSNA 2022 Cervical Spine Fracture Detection competition demonstrated high performance on a large clinical test set of emergency department cervical spine CT scans from a level I trauma center.
View article: Image segmentations produced by BAMF under the AIMI Annotations initiative
Image segmentations produced by BAMF under the AIMI Annotations initiative Open
The Imaging Data Commons (IDC)(https://imaging.datacommons.cancer.gov/) [1] connects researchers with publicly available cancer imaging data, often linked with other types of cancer data. Many of the collections have limited annotations du…
View article: The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset
The RSNA Abdominal Traumatic Injury CT (RATIC) Dataset Open
The RSNA Abdominal Traumatic Injury CT (RATIC) dataset is the largest publicly available collection of adult abdominal CT studies annotated for traumatic injuries. This dataset includes 4,274 studies from 23 institutions across 14 countrie…
View article: Erratum for: Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge
Erratum for: Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge Open
View article: Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges Open
The Radiological Society of North America (RSNA) has held artificial intelligence competitions to tackle real-world medical imaging problems at least annually since 2017. This article examines the challenges and processes involved in organ…
View article: Vision Transformer–based Decision Support for Neurosurgical Intervention in Acute Traumatic Brain Injury: Automated Surgical Intervention Support Tool
Vision Transformer–based Decision Support for Neurosurgical Intervention in Acute Traumatic Brain Injury: Automated Surgical Intervention Support Tool Open
Purpose To develop an automated triage tool to predict neurosurgical intervention for patients with traumatic brain injury (TBI). Materials and Methods A provincial trauma registry was reviewed to retrospectively identify patients with TBI…
View article: Machine Learning Detection and Characterization of Splenic Injuries on Abdominal Computed Tomography
Machine Learning Detection and Characterization of Splenic Injuries on Abdominal Computed Tomography Open
Background: Multi-detector contrast-enhanced abdominal computed tomography (CT) allows for the accurate detection and classification of traumatic splenic injuries, leading to improved patient management. Their effective use requires rapid …
View article: Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge
Performance of the Winning Algorithms of the RSNA 2022 Cervical Spine Fracture Detection Challenge Open
Purpose To evaluate and report the performance of the winning algorithms of the Radiological Society of North America Cervical Spine Fracture AI Challenge. Materials and Methods The competition was open to the public on Kaggle from July 28…
View article: Data Liberation and Crowdsourcing in Medical Research: The Intersection of Collective and Artificial Intelligence
Data Liberation and Crowdsourcing in Medical Research: The Intersection of Collective and Artificial Intelligence Open
In spite of an exponential increase in the volume of medical data produced globally, much of these data are inaccessible to those who might best use them to develop improved health care solutions through the application of advanced analyti…
View article: The RSNA Cervical Spine Fracture CT Dataset
The RSNA Cervical Spine Fracture CT Dataset Open
This dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/.
View article: Insights on the Current State and Future Outlook of AI in Health Care: Expert Interview Study
Insights on the Current State and Future Outlook of AI in Health Care: Expert Interview Study Open
Background Artificial intelligence (AI) is often promoted as a potential solution for many challenges health care systems face worldwide. However, its implementation in clinical practice lags behind its technological development. Objective…
View article: The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting Open
A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition time series typically starts with an already pathological sca…
View article: Augmentation of the RSNA Pulmonary Embolism CT Dataset with Bounding Box Annotations and Anatomic Localization of Pulmonary Emboli
Augmentation of the RSNA Pulmonary Embolism CT Dataset with Bounding Box Annotations and Anatomic Localization of Pulmonary Emboli Open
Supplemental material is available for this article. Keywords: CT, Pulmonary Arteries, Embolism/Thrombosis, Feature Detection © RSNA, 2023.
View article: BenchMD: A Benchmark for Unified Learning on Medical Images and Sensors
BenchMD: A Benchmark for Unified Learning on Medical Images and Sensors Open
Medical data poses a daunting challenge for AI algorithms: it exists in many different modalities, experiences frequent distribution shifts, and suffers from a scarcity of examples and labels. Recent advances, including transformers and se…
View article: AI Models Close to your Chest: Robust Federated Learning Strategies for Multi-site CT
AI Models Close to your Chest: Robust Federated Learning Strategies for Multi-site CT Open
While it is well known that population differences from genetics, sex, race, and environmental factors contribute to disease, AI studies in medicine have largely focused on locoregional patient cohorts with less diverse data sources. Such …
View article: Insights on the Current State and Future Outlook of AI in Health Care: Expert Interview Study (Preprint)
Insights on the Current State and Future Outlook of AI in Health Care: Expert Interview Study (Preprint) Open
BACKGROUND Artificial intelligence (AI) is often promoted as a potential solution for many challenges health care systems face worldwide. However, its implementation in clinical practice lags behind its technological development. OBJECT…
View article: Standardized Reporting on the Preoperative CT Assessment of Potential Living Renal Transplant Donors: Can We Create a Universal Report Standard to Meet the Needs of Transplant Urologists?
Standardized Reporting on the Preoperative CT Assessment of Potential Living Renal Transplant Donors: Can We Create a Universal Report Standard to Meet the Needs of Transplant Urologists? Open
Purpose: Determine whether standardized template reporting for the preoperative assessment of potential living renal transplant donors improves the comprehensiveness of radiology reports to meet the needs of urologists performing renal tra…
View article: Non-task expert physicians benefit from correct explainable AI advice when reviewing X-rays
Non-task expert physicians benefit from correct explainable AI advice when reviewing X-rays Open
View article: Infection complications after transrectal ultrasound-guided prostate biopsy: A radiology department’s experience and strategy for improvement
Infection complications after transrectal ultrasound-guided prostate biopsy: A radiology department’s experience and strategy for improvement Open
Introduction: Transrectal ultrasound (TRUS)-guided prostate biopsy is a common procedure performed to diagnose prostate cancer. The risk of infection complications is well-described in the literature, and strategies to avoid such complicat…
View article: Who should do as AI say? Only non-task expert physicians benefit from correct explainable AI advice
Who should do as AI say? Only non-task expert physicians benefit from correct explainable AI advice Open
Artificial intelligence (AI)-generated clinical advice is becoming more prevalent in healthcare. However, the impact of AI-generated advice on physicians’ decision-making is underexplored. In this study, physicians received X-rays with cor…