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, 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
2016
MRI-US fusion targeted biopsy results in patients with a history of a prior negative biopsy.
Nawaf C, Lu A, Rosoff J, Weinreb J, Schulam P, Humphrey P, Levi A, Sprenkle P. MRI-US fusion targeted biopsy results in patients with a history of a prior negative biopsy. Journal Of Clinical Oncology 2016, 34: 90-90. DOI: 10.1200/jco.2016.34.2_suppl.90.Peer-Reviewed Original ResearchPrior negative biopsyCS cancerGleason scoreNegative MRIProstate cancerNegative biopsyCS prostate cancerMRI suspicion scoreMRI-US fusionPre-biopsy mpMRIFusion prostate biopsyMRI-ultrasound fusionSignificant prostate cancerCancer detection rateBiopsy of lesionsMaximum Gleason scoreMulti-parametric MRIElevated PSAPrevious biopsyRepeat biopsyMapping biopsyBiopsy resultsProstate biopsyFusion biopsyStandard biopsy
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