A5022563719- Acute Ischemic Stroke Management
- Cerebrovascular and Carotid Artery Diseases
- Intracranial Aneurysms: Treatment and Complications
- Venous Thromboembolism Diagnosis and Management
- Stroke Rehabilitation and Recovery
- Cardiac, Anesthesia and Surgical Outcomes
- Vascular Malformations Diagnosis and Treatment
- Traumatic Brain Injury and Neurovascular Disturbances
- Radiomics and Machine Learning in Medical Imaging
- Intracerebral and Subarachnoid Hemorrhage Research
- Diversity and Career in Medicine
- Radiology practices and education
- Artificial Intelligence in Healthcare and Education
- Machine Learning in Healthcare
- Hip and Femur Fractures
- Peripheral Artery Disease Management
- Pelvic and Acetabular Injuries
- COVID-19 and healthcare impacts
- Appendicitis Diagnosis and Management
- Topic Modeling
- Trauma and Emergency Care Studies
- Cardiac pacing and defibrillation studies
- Industrial Vision Systems and Defect Detection
- Brain Tumor Detection and Classification
- Surgical site infection prevention
Mayo Clinic in Arizona
2021-2025
Mayo Clinic
2022-2025
Duke University Hospital
2025
WinnMed
2022-2025
Piedmont International University
2024
Duke University
2024
University of Pennsylvania
2023-2024
Duke University Health System
2024
National Institute for Health Research
2024
University of Birmingham
2024
Mechanical thrombectomy greatly improves stroke outcomes. Nonetheless, some patients fall short of full recovery despite good reperfusion. The purpose this study was to develop machine learning (ML) models for the pre-interventional prediction functional outcome at 3 months in acute ischemic (AIS), using clinical and auto-extractable radiological information consistently available upon first emergency evaluation.A two-center retrospective cohort 293 with AIS who underwent analyzed. ML were...
“Just Accepted” papers have undergone full peer review and been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, proof before it is published its final version. Please note that during production of the copyedited article, errors may be discovered which could affect content. Purpose To develop evaluate an automated system extracting structured clinical information from unstructured radiology pathology reports using open-weights...
Stroke is a major cause of mortality and permanent disability worldwide. Precise prediction post-stroke essential for guiding treatment decisions rehabilitation planning. The ability Machine learning models to process large amounts data, offer promising alternative improving in stroke patients. In this review, we aim evaluate the risk bias different machine used predicting mortality. This review was conducted following Preferred Reporting Items Systematic Reviews Meta-Analyses (PRISMA)...
Abstract While the Woven EndoBridge (WEB) device has transformed treatment of wide-neck intracranial aneurysms, incomplete occlusion remains a significant challenge requiring better understanding contributing factors. A retrospective analysis was conducted on multicenter data from patients who underwent WEB for aneurysms between January 2011 and December 2022. Using machine learning models, Cox regression, time-stratified analyses, we evaluated factors associated with persistent occlusion,...
Abstract Study Objectives To investigate sleep patterns in the camel by combining behavioral and polysomnography (PSG) methods. Methods A noninvasive PSG study was conducted over four nights on animals. Additionally, video recordings were used to monitor behaviors associated with different vigilance states. Results During night, short periods of sporadic sleep-like behavior corresponding a specific posture, sternal recumbency (SR) head lying down ground, observed. The results showed rapid...
Delayed Cerebral Ischemia (DCI) is a significant complication following aneurysmal subarachnoid hemorrhage (aSAH) that can lead to poor outcomes. Machine learning techniques have shown promise in predicting DCI and improving risk stratification.
Computed tomography (CT) angiography collateral score (CTA-CS) is an important clinical outcome predictor following mechanical thrombectomy for ischemic stroke with large vessel occlusion (LVO). The present multireader study aimed to evaluate the performance of e-CTA software automated assistance in CTA-CS scoring.
Introduction Various clinical trials addressing large core acute ischemic stroke (AIS) are ongoing from multiple international groups. Future development of guidelines depends on meta‐analyses these calling for a degree homogeneity elements across the different studies. The aim this common data element study was to provide an overview key features pertinent infarct trials. Methods PubMed and ClinicalTrials.gov databases were screened published assessing mechanical thrombectomy in patients...
Abstract Background: Heart failure (HF) is a growing health concern among the elderly. Although NT-proBNP valuable biomarker for diagnosing HF, its levels are not easy to interpret in older subjects because of age-related increases. Previous data indicates that above 450.0 pg/mL patients aged 75 and may indicate heart failure. This study aims assess significance mildly increased individuals older, examining their correlation echocardiographic results, associated risk factors, clinical...