Academic Radiology

Papers
(The H4-Index of Academic Radiology is 40. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-03-01 to 2024-03-01.)
ArticleCitations
Coronavirus Disease (COVID-19): Spectrum of CT Findings and Temporal Progression of the Disease182
Medical 3D Printing Cost-Savings in Orthopedic and Maxillofacial Surgery: Cost Analysis of Operating Room Time Saved with 3D Printed Anatomic Models and Surgical Guides137
Olfactory Bulb MRI and Paranasal Sinus CT Findings in Persistent COVID-19 Anosmia133
Imaging Features of Coronavirus disease 2019 (COVID-19): Evaluation on Thin-Section CT123
Olfactory Bulb Magnetic Resonance Imaging in SARS-CoV-2-Induced Anosmia: The First Report109
Creating Artificial Images for Radiology Applications Using Generative Adversarial Networks (GANs) – A Systematic Review90
A Machine Learning Algorithm to Estimate Sarcopenia on Abdominal CT84
18FDG PET/CT Scan Reveals Hypoactive Orbitofrontal Cortex in Anosmia of COVID-1979
Medical Student Education Roadblock Due to COVID-19: Virtual Radiology Core Clerkship to the Rescue73
Video Interviewing: A Review and Recommendations for Implementation in the Era of COVID-19 and Beyond70
CT Quantification and Machine-learning Models for Assessment of Disease Severity and Prognosis of COVID-19 Patients69
Lymphadenopathy Following COVID-19 Vaccination: Imaging Findings Review66
COVID-19 Impact on Well-Being and Education in Radiology Residencies: A Survey of the Association of Program Directors in Radiology66
Acute Mesenteric Ischemia in Severe Coronavirus-19 (COVID-19): Possible Mechanisms and Diagnostic Pathway63
Virtual Read-Out: Radiology Education for the 21st Century During the COVID-19 Pandemic62
Contrast-Enhanced Abdominal CT with Clinical Photon-Counting Detector CT: Assessment of Image Quality and Comparison with Energy-Integrating Detector CT57
Radiology Residency Preparedness and Response to the COVID-19 Pandemic57
3D Printed Face Shields: A Community Response to the COVID-19 Global Pandemic56
CT Radiomics Signature of Tumor and Peritumoral Lung Parenchyma to Predict Nonsmall Cell Lung Cancer Postsurgical Recurrence Risk56
COVID-19 Pandemic Impact on Decreased Imaging Utilization: A Single Institutional Experience55
Infection Control against COVID-19 in Departments of Radiology54
Corona Virus International Public Health Emergencies: Implications for Radiology Management52
Assessment of Small Pulmonary Blood Vessels in COVID-19 Patients Using HRCT51
Deep Myometrial Infiltration of Endometrial Cancer on MRI: A Radiomics-Powered Machine Learning Pilot Study51
Burnout in Academic Radiologists in the United States51
Assessment of the Willingness of Radiologists and Radiographers to Accept the Integration of Artificial Intelligence Into Radiology Practice50
CT Manifestations and Clinical Characteristics of 1115 Patients with Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-analysis50
Innovation Born in Isolation: Rapid Transformation of an In-Person Medical Student Radiology Elective to a Remote Learning Experience During the COVID-19 Pandemic50
Noninterpretive Uses of Artificial Intelligence in Radiology49
FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies48
Radiology Education in the Time of COVID-19: A Novel Distance Learning Workstation Experience for Residents48
Utility of Artificial Intelligence Tool as a Prospective Radiology Peer Reviewer — Detection of Unreported Intracranial Hemorrhage48
Brave New World: Challenges and Opportunities in the COVID-19 Virtual Interview Season46
Prediction of Benign and Malignant Solid Renal Masses: Machine Learning-Based CT Texture Analysis44
AI-RADS: An Artificial Intelligence Curriculum for Residents44
Quality of Prostate MRI: Is the PI-RADS Standard Sufficient?43
Trainee and Attending Perspectives on Remote Radiology Readouts in the Era of the COVID-19 Pandemic43
Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Carcinoma Using Radiomics Features Based on the Fat-Suppressed T2 Sequence42
Ultrasound-Based Radiomic Nomogram for Predicting Lateral Cervical Lymph Node Metastasis in Papillary Thyroid Carcinoma41
COVID-19 Evaluation by Low-Dose High Resolution CT Scans Protocol40
The Diagnostic Value of MRI for Preoperative Staging in Patients with Endometrial Cancer: A Meta-Analysis40
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