A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology–Radiology Fusion

Author:

Khosravi Pegah123ORCID,Lysandrou Maria4,Eljalby Mahmoud5,Li Qianzi26,Kazemi Ehsan7,Zisimopoulos Pantelis23,Sigaras Alexandros23,Brendel Matthew2,Barnes Josue23,Ricketts Camir23,Meleshko Dmitry23,Yat Andy8,McClure Timothy D.5,Robinson Brian D.9,Sboner Andrea239,Elemento Olivier2310,Chughtai Bilal5,Hajirasouliha Iman23

Affiliation:

1. Computational Oncology, Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York New York USA

2. Department of Physiology and Biophysics Institute for Computational Biomedicine, Weill Cornell Medicine of Cornell University New York New York USA

3. Caryl and Israel Englander Institute for Precision Medicine The Meyer Cancer Center, Weill Cornell Medicine New York New York USA

4. Neuroscience Institute The University of Chicago Chicago Illinois USA

5. Department of Urology Weill Cornell Medicine of Cornell University New York New York USA

6. Mathematics and Statistics Department Carleton College Northfield Minnesota USA

7. Yale University, Department of Electrical Engineering

8. Department of Radiology New York‐Presbyterian Hospital New York New York USA

9. Department of Pathology New York Presbyterian Hospital‐Weill Cornell Medical College New York New York USA

10. WorldQuant Initiative for Quantitative Prediction Weill Cornell Medicine New York New York USA

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging

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