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Medicine

D-Index
98
Citations
39381
World Ranking
8867
National Ranking
4567

Overview

Baris Turkbey is affiliated with the National Institutes of Health in the United States. Their research primarily focuses on medical and clinical applications, especially within the field of medicine.

The main fields of study for Baris Turkbey include:

  • Medicine

Within medicine, their subfields of study consist of:

  • Pulmonary and Respiratory Medicine
  • Radiology, Nuclear Medicine and Imaging
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Surgery

The key topics covered in Baris Turkbey's body of work are:

  • Prostate Cancer Diagnosis and Treatment
  • Prostate Cancer Treatment and Research
  • Radiomics and Machine Learning in Medical Imaging
  • MRI in cancer diagnosis
  • Urologic and reproductive health conditions
  • AI in cancer detection
  • COVID-19 diagnosis using AI

Baris Turkbey has contributed to a number of publications in notable venues, frequently publishing in the following journals and platforms:

  • The Journal of Urology
  • Journal of Clinical Oncology
  • arXiv (Cornell University)
  • Academic Radiology
  • Radiology

Among the recent papers associated with Baris Turkbey are:

  • "MRI-Targeted, Systematic, and Combined Biopsy for Prostate Cancer Diagnosis," 2020, New England Journal of Medicine
  • "Federated learning for predicting clinical outcomes in patients with COVID-19," 2021, Nature Medicine
  • "Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets," 2020, Nature Communications
  • "Generalizing Deep Learning for Medical Image Segmentation to Unseen Domains via Deep Stacked Transformation," 2020, IEEE Transactions on Medical Imaging
  • "Variability of the Positive Predictive Value of PI-RADS for Prostate MRI across 26 Centers: Experience of the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel," 2020, Radiology

Frequent co-authorship in Baris Turkbey's research includes collaboration with:

  • Peter L. Choyke
  • Bradford J. Wood
  • Peter A. Pinto
  • Stephanie A. Harmon
  • Maria J. Merino

Best Publications

  • Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2.

    Baris Turkbey;Andrew B. Rosenkrantz;Masoom A. Haider;Anwar R. Padhani

  • Comparison of MR/Ultrasound Fusion–Guided Biopsy With Ultrasound-Guided Biopsy for the Diagnosis of Prostate Cancer

    M. Minhaj Siddiqui;M. Minhaj Siddiqui;Soroush Rais-Bahrami;Soroush Rais-Bahrami;Baris Turkbey;Arvin K. George

  • MRI-Targeted, Systematic, and Combined Biopsy for Prostate Cancer Diagnosis

    Michael Ahdoot;Andrew R Wilbur;Sarah E Reese;Amir H Lebastchi

  • Federated learning for predicting clinical outcomes in patients with COVID-19.

    Ittai Dayan;Holger R. Roth;Aoxiao Zhong;Ahmed Harouni

  • Multiparametric 3T prostate magnetic resonance imaging to detect cancer: histopathological correlation using prostatectomy specimens processed in customized magnetic resonance imaging based molds

    Baris Turkbey;Haresh Mani;Vijay Shah;Vijay Shah;Ardeshir R. Rastinehad

  • Magnetic Resonance Imaging/Ultrasound Fusion Guided Prostate Biopsy Improves Cancer Detection Following Transrectal Ultrasound Biopsy and Correlates With Multiparametric Magnetic Resonance Imaging

    Peter A. Pinto;Paul H. Chung;Ardeshir R. Rastinehad;Angelo A. Baccala

  • Prostate cancer: value of multiparametric MR imaging at 3 T for detection--histopathologic correlation.

    Baris Turkbey;Peter A. Pinto;Haresh Mani;Marcelino Bernardo

  • Artificial intelligence for the detection of COVID-19 pneumonia on chest CT using multinational datasets.

    Stephanie A. Harmon;Thomas H. Sanford;Sheng Xu;Evrim B. Turkbey

  • Magnetic Resonance Imaging/Ultrasound-Fusion Biopsy Significantly Upgrades Prostate Cancer Versus Systematic 12-core Transrectal Ultrasound Biopsy

    M. Minhaj Siddiqui;Soroush Rais-Bahrami;Hong Truong;Lambros Stamatakis

  • Interobserver Reproducibility of the PI-RADS Version 2 Lexicon: A Multicenter Study of Six Experienced Prostate Radiologists.

    Andrew B. Rosenkrantz;Luke A. Ginocchio;Daniel Cornfeld;Adam T. Froemming

  • Generalizing Deep Learning for Medical Image Segmentation to Unseen Domains via Deep Stacked Transformation

    Ling Zhang;Xiaosong Wang;Dong Yang;Thomas Sanford

  • Standards of Reporting for MRI-targeted Biopsy Studies (START) of the Prostate: Recommendations from an International Working Group.

    Caroline M. Moore;Veeru Kasivisvanathan;Scott Eggener;Mark Emberton

  • Is apparent diffusion coefficient associated with clinical risk scores for prostate cancers that are visible on 3-T MR images?

    Baris Turkbey;Vijay P. Shah;Yuxi Pang;Marcelino Bernardo

  • Prostate Cancer: Interobserver Agreement and Accuracy with the Revised Prostate Imaging Reporting and Data System at Multiparametric MR Imaging.

    Berrend G. Muller;Joanna H. Shih;Sandeep Sankineni;Jamie Marko;Jamie Marko

  • Overview of Dynamic Contrast-Enhanced MRI in Prostate Cancer Diagnosis and Management

    Sadhna Verma;Baris Turkbey;Naira Muradyan;Arumugam Rajesh

  • Real-time MRI-TRUS fusion for guidance of targeted prostate biopsies.

    Sheng Xu;Jochen Kruecker;Baris Turkbey;Neil Glossop

  • Multiparametric Magnetic Resonance Imaging and Ultrasound Fusion Biopsy Detect Prostate Cancer in Patients with Prior Negative Transrectal Ultrasound Biopsies

    Srinivas Vourganti;Ardeshir Rastinehad;Nitin K. Yerram;Jeffrey Nix

  • Variability of the positive predictive value of PI-RADS for prostate MRI across 26 centers: Experience of the society of abdominal radiology prostate cancer disease-focused panel

    Antonio C. Westphalen;Charles E. McCulloch;Jordan M. Anaokar;Sandeep Arora

  • Intravoxel incoherent motion MR imaging for prostate cancer: An evaluation of perfusion fraction and diffusion coefficient derived from different b-value combinations

    Yuxi Pang;Baris Turkbey;Marcelino Bernardo;Jochen Kruecker

  • Review of functional/anatomical imaging in oncology.

    Stephanie N. Histed;Maria L. Lindenberg;Esther Mena;Baris Turkbey

Frequent Co-Authors

Peter L. Choyke
Peter L. Choyke National Institutes of Health
Bradford J. Wood
Bradford J. Wood National Institutes of Health
Peter A. Pinto
Peter A. Pinto National Institutes of Health
Maria J. Merino
Maria J. Merino National Institutes of Health
Pingkun Yan
Pingkun Yan Rensselaer Polytechnic Institute
Ronald M. Summers
Ronald M. Summers National Institutes of Health
W. Marston Linehan
W. Marston Linehan National Institutes of Health
James L. Gulley
James L. Gulley National Institutes of Health
Holger R. Roth
Holger R. Roth Nvidia (United States)
Daguang Xu
Daguang Xu Nvidia (United Kingdom)

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