Maya B. Wolf

A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis

Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study

The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) Statement

Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment

Preparing Medical Imaging Data for Machine Learning

High-Voltage Electrical Pulses in Oncology: Irreversible Electroporation, Electrochemotherapy, Gene Electrotransfer, Electrofusion, and Electroimmunotherapy

Irreversible Electroporation for Colorectal Liver Metastases

PI-RADS Prostate Imaging – Reporting and Data System: 2015, Version 2

Using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement to Assess Reporting of Observational Trials in Hand Surgery

Photothermal therapy and photoacoustic imaging via nanotheranostics in fighting cancer

Joint Prostate Cancer Detection and Gleason Score Prediction in mp-MRI via FocalNet

Accuracy of Multiparametric MRI for Prostate Cancer Detection: A Meta-Analysis

Recent advances in carbon based nanosystems for cancer theranostics

Multiparametric Magnetic Resonance Imaging (MRI) and MRI–Transrectal Ultrasound Fusion Biopsy for Index Tumor Detection: Correlation with Radical Prostatectomy Specimen

Capsular Imbrication for Posttraumatic Instability of the Distal Radioulnar Joint

Dynamic contrast enhanced MRI monitoring of primary proton and carbon ion irradiation of prostate cancer using a novel hypofractionated raster scan technique

Specific CT 3D rendering of the treatment zone after Irreversible Electroporation (IRE) in a pig liver model: the “Chebyshev Center Concept” to define the maximum treatable tumor size

The Impact of Magnetic Resonance Imaging on Prediction of Extraprostatic Extension and Prostatectomy Outcome in Patients with Low-, Intermediate- and High-Risk Prostate Cancer: Try to Find a Standard