Rakesh Shiradkar

1.1k total citations
38 papers, 720 citations indexed

About

Rakesh Shiradkar is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Rakesh Shiradkar has authored 38 papers receiving a total of 720 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Radiology, Nuclear Medicine and Imaging, 25 papers in Pulmonary and Respiratory Medicine and 5 papers in Oncology. Recurrent topics in Rakesh Shiradkar's work include Radiomics and Machine Learning in Medical Imaging (32 papers), Prostate Cancer Diagnosis and Treatment (23 papers) and Prostate Cancer Treatment and Research (15 papers). Rakesh Shiradkar is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (32 papers), Prostate Cancer Diagnosis and Treatment (23 papers) and Prostate Cancer Treatment and Research (15 papers). Rakesh Shiradkar collaborates with scholars based in United States, Finland and Australia. Rakesh Shiradkar's co-authors include Anant Madabhushi, Andrei S. Purysko, Ivan Jambor, Soumya Ghose, Lee Ponsky, Ahmad Algohary, Pekka Taimen, Otto Ettala, Amr Mahran and Satish E. Viswanath and has published in prestigious journals such as Circulation, Journal of Clinical Oncology and Scientific Reports.

In The Last Decade

Rakesh Shiradkar

33 papers receiving 718 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Rakesh Shiradkar United States	12	604	407	142	121	68	38	720
Ece Ateş Kuş Türkiye	11	635 1.1×	320 0.8×	116 0.8×	186 1.5×	99 1.5×	15	731
Xingyu Zhao China	14	519 0.9×	251 0.6×	147 1.0×	108 0.9×	69 1.0×	31	670
Ahmad Algohary United States	8	367 0.6×	274 0.7×	75 0.5×	84 0.7×	40 0.6×	16	440
M Jermoumi United States	4	586 1.0×	241 0.6×	115 0.8×	228 1.9×	99 1.5×	9	668
Sarah A. Mattonen Canada	13	796 1.3×	457 1.1×	171 1.2×	214 1.8×	138 2.0×	36	963
Mostafa Nazari Iran	11	498 0.8×	227 0.6×	103 0.7×	188 1.6×	52 0.8×	18	562
Lianzhen Zhong China	15	711 1.2×	389 1.0×	155 1.1×	103 0.9×	208 3.1×	22	934
Yubao Guan China	16	412 0.7×	459 1.1×	96 0.7×	98 0.8×	107 1.6×	49	694
Elisabeth Pfaehler Netherlands	15	649 1.1×	252 0.6×	67 0.5×	186 1.5×	105 1.5×	31	721
Junming Jian China	13	527 0.9×	206 0.5×	147 1.0×	133 1.1×	92 1.4×	22	624

Countries citing papers authored by Rakesh Shiradkar

Since Specialization

Citations

This map shows the geographic impact of Rakesh Shiradkar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Rakesh Shiradkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rakesh Shiradkar more than expected).

Fields of papers citing papers by Rakesh Shiradkar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rakesh Shiradkar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Rakesh Shiradkar. The network helps show where Rakesh Shiradkar may publish in the future.

Co-authorship network of co-authors of Rakesh Shiradkar

This figure shows the co-authorship network connecting the top 25 collaborators of Rakesh Shiradkar. A scholar is included among the top collaborators of Rakesh Shiradkar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Rakesh Shiradkar. Rakesh Shiradkar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Shiradkar, Rakesh, et al.. (2025). Automated Knowledge Graph Construction using Large Language Models and Sentence Complexity Modelling. 15526–15550.

Guha, Avirup, Viraj Shah, Omar Mohamed Makram, et al.. (2025). Artificial Intelligence Applications in Cardio-Oncology: A Comprehensive Review. Current Cardiology Reports. 27(1). 56–56. 8 indexed citations

Midya, Abhishek, Sree Harsha Tirumani, Leonardo Kayat Bittencourt, et al.. (2025). Population-Specific Radiomics From Biparametric Magnetic Resonance Imaging Improves Prostate Cancer Risk Stratification in African American Men. JU Open Plus. 3(7).

Viswanathan, Vidya Sankar, Kaustav Bera, Rakesh Shiradkar, et al.. (2024). Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study. Computers in Biology and Medicine. 177. 108643–108643. 4 indexed citations

Banerjee, Imon, John L. Burns, Hari Trivedi, et al.. (2023). “Shortcuts” Causing Bias in Radiology Artificial Intelligence: Causes, Evaluation, and Mitigation. Journal of the American College of Radiology. 20(9). 842–851. 37 indexed citations

Li, Lin, Rakesh Shiradkar, Vidya Sankar Viswanathan, et al.. (2023). Multi‐scale statistical deformation based co‐registration of prostate MRI and post‐surgical whole mount histopathology. Medical Physics. 51(4). 2549–2562. 1 indexed citations

Steinberg, Rebecca, Leo Anthony Celi, Saptarshi Purkayastha, et al.. (2023). Identifying and improving the “ground truth” of race in disparities research through improved EMR data reporting. A systematic review. International Journal of Medical Informatics. 182. 105303–105303. 4 indexed citations

Steinberg, Rebecca, Leo Anthony Celi, Saptarshi Purkayastha, et al.. (2023). Identifying and Improving the 'Ground Truth' of Race in Disparities Research Through Improved EMR Data Reporting. A Systematic Review. SSRN Electronic Journal. 1 indexed citations

Chicco, Davide & Rakesh Shiradkar. (2023). Ten quick tips for computational analysis of medical images. PLoS Computational Biology. 19(1). e1010778–e1010778. 11 indexed citations

10.

Shiradkar, Rakesh, Sree Harsha Tirumani, Leonardo Kayat Bittencourt, et al.. (2023). Novel radiomic analysis on bi-parametric MRI for characterizing differences between MR non-visible and visible clinically significant prostate cancer. European Journal of Radiology Open. 10. 100496–100496. 2 indexed citations

11.

Shiradkar, Rakesh, Soumya Ghose, Amr Mahran, et al.. (2022). Prostate Surface Distension and Tumor Texture Descriptors From Pre-Treatment MRI Are Associated With Biochemical Recurrence Following Radical Prostatectomy: Preliminary Findings. Frontiers in Oncology. 12. 841801–841801. 14 indexed citations

12.

Shiradkar, Rakesh, Pingfu Fu, Amr Mahran, et al.. (2021). 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. The Lancet Digital Health. 3(7). e445–e454. 75 indexed citations

13.

Shiradkar, Rakesh, Ananya Panda, Patrick Leo, et al.. (2020). Correction to: 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. European Radiology. 31(4). 2644–2644. 1 indexed citations

14.

Shiradkar, Rakesh, Ananya Panda, Patrick Leo, et al.. (2020). 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. European Radiology. 31(3). 1336–1346. 32 indexed citations

15.

Shiradkar, Rakesh, Harri Merisaari, Prateek Prasanna, et al.. (2020). Test-retest repeatability of a deep learning architecture in detecting and segmenting clinically significant prostate cancer on apparent diffusion coefficient (ADC) maps. European Radiology. 31(1). 379–391. 22 indexed citations

16.

Li, Lin, Rakesh Shiradkar, Patrick Leo, et al.. (2020). A novel imaging based Nomogram for predicting post-surgical biochemical recurrence and adverse pathology of prostate cancer from pre-operative bi-parametric MRI. EBioMedicine. 63. 103163–103163. 44 indexed citations

17.

Ghose, Soumya, Rakesh Shiradkar, Mirabela Rusu, et al.. (2017). Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings. Scientific Reports. 7(1). 15829–15829. 9 indexed citations

18.

Shiradkar, Rakesh, Tarun K. Podder, Ahmad Algohary, et al.. (2016). Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI. Radiation Oncology. 11(1). 148–148. 73 indexed citations

19.

Shiradkar, Rakesh, et al.. (2014). A New Perspective on Material Classification and Ink Identification. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 9 indexed citations

20.

Shiradkar, Rakesh, Ping Tan, & Sim Heng Ong. (2014). Auto-calibrating photometric stereo using ring light constraints. Machine Vision and Applications. 25(3). 801–809. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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