Rakesh Shiradkar - Concepedia

Author

Rakesh Shiradkar

Case Western Reserve University ORCID

Also Known As

R. Shiradkar, Rakesh Shiradkar, Rakesh Shiradkar*, Shiradkar, Rakesh

Publications

Citations

H-Index

Concepts

All Affiliations

Case Western Reserve University Cleveland Clinic University Hospitals of Cleveland Icahn School of Medicine at Mount Sinai University of Turku

About

Rakesh Shiradkar is an author at Case Western Reserve University specializing in biomedical imaging, digital pathology, and radiology.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	3	3	60
2	Medicine	2	2	70
3	Health Sciences	1	1	40
4	Public Health	1	1	17
5	Biostatistics	1	1	17

Rakesh Shiradkar

Publications

800

Citations

H-Index

Page 1

	Year	Citations
Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings Rakesh Shiradkar, Soumya Ghose, Ivan Jambor, Journal of Magnetic Resonance Imaging	2018	138
Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings Ahmad Algohary, Satish E. Viswanath, Rakesh Shiradkar, Journal of Magnetic Resonance Imaging	2018	111
An integrated nomogram combining deep learning, Prostate Imaging–Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study Amogh Hiremath, Rakesh Shiradkar, Pingfu Fu, The Lancet Digital Health	2021	109
Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI Rakesh Shiradkar, Tarun K. Podder, Ahmad Algohary, Radiation Oncology	2016	94
Combination of Peri-Tumoral and Intra-Tumoral Radiomic Features on Bi-Parametric MRI Accurately Stratifies Prostate Cancer Risk: A Multi-Site Study Ahmad Algohary, Rakesh Shiradkar, Shivani Pahwa, Cancers	2020	80
A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI Lin Li, Rakesh Shiradkar, Patrick Leo, EBioMedicine	2020	61
T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning–derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount histopathology Rakesh Shiradkar, Ananya Panda, Patrick Leo, European Radiology Urogenital RadiologyStain NormalizationUrologyT2 MrMedical Imaging	2020	40
Repeatability of radiomics and machine learning for DWI: Short‐term repeatability study of 112 patients with prostate cancer Harri Merisaari, Pekka Taimen, Rakesh Shiradkar, Magnetic Resonance in Medicine	2019	36
Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps Amogh Hiremath, Rakesh Shiradkar, Harri Merisaari, European Radiology Significant Prostate CancerUrologyImage AnalysisMachine LearningMedical Imaging	2020	30
Computer extracted gland features from H&E predicts prostate cancer recurrence comparably to a genomic companion diagnostic test: a large multi-site study Patrick Leo, Andrew Janowczyk, Robin Elliott, npj Precision Oncology	2021	26

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