Michael Spektor, MD
Associate Professor of Radiology and Biomedical ImagingCards
About
Research
Publications
2025
Comparative Performance of Machine Learning Models in Reducing Unnecessary Targeted Prostate Biopsies
Chen F, Esmaili R, Khajir G, Zeevi T, Gross M, Leapman M, Sprenkle P, Justice A, Arora S, Weinreb J, Spektor M, Huber S, Humphrey P, Levi A, Staib L, Venkataraman R, Martin D, Onofrey J. Comparative Performance of Machine Learning Models in Reducing Unnecessary Targeted Prostate Biopsies. European Urology Oncology 2025 PMID: 39924390, PMCID: PMC12332026, DOI: 10.1016/j.euo.2025.01.005.Peer-Reviewed Original ResearchProstate cancerPrediction of clinically significant prostate cancerClinical dataProstate-specific antigen levelClinically Significant Prostate CancerProstate magnetic resonance imagingSeverity of prostate cancerCombination of clinical featuresPrediction of csPCaSignificant prostate cancerProstate Imaging-ReportingCore needle biopsyRetrospective analysis of dataDecision curve analysisReducing unnecessary biopsiesProstate cancer diagnosisReceiver operating characteristic curveArea under the receiver operating characteristic curveFalse-negative rateMagnetic resonance imagingPersonalized risk assessmentAntigen levelsNeedle biopsyPatient ageUnnecessary biopsies
Academic Achievements & Community Involvement
Clinical Care
Overview
Michael Spektor, MD, is a radiologist specializing in abdominal and pelvic imaging. He diagnoses and images a wide range of conditions, with specific expertise in body CT, MRI, fluoroscopy, and ultrasound. He uses advanced imaging techniques to interpret images of internal organs.
As an associate professor of radiology and biomedical imaging at Yale School of Medicine, Dr. Spektor is involved in research that seeks to improve imaging methodologies and enhance diagnostic accuracy.
Dr. Spektor received his medical degree from Albert Einstein College of Medicine, followed by an internship in internal medicine at Winthrop University Hospital, and residency in diagnostic radiology at NSLIJ. He further honed his expertise with a fellowship in body MRI at Yale University.
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