Patrick Leo

883 total citations
31 papers, 464 citations indexed

About

Patrick Leo is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Patrick Leo has authored 31 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Pulmonary and Respiratory Medicine and 11 papers in Artificial Intelligence. Recurrent topics in Patrick Leo's work include Radiomics and Machine Learning in Medical Imaging (20 papers), Prostate Cancer Diagnosis and Treatment (11 papers) and AI in cancer detection (11 papers). Patrick Leo is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (20 papers), Prostate Cancer Diagnosis and Treatment (11 papers) and AI in cancer detection (11 papers). Patrick Leo collaborates with scholars based in United States, Switzerland and China. Patrick Leo's co-authors include Anant Madabhushi, Robin Elliott, Michael D. Feldman, Pingfu Fu, George Lee, Natalie Shih, Andrew Janowczyk, Kaustav Bera, Germán Corredor and Vamsidhar Velcheti and has published in prestigious journals such as Journal of Clinical Oncology, Scientific Reports and Clinical Cancer Research.

In The Last Decade

Patrick Leo

30 papers receiving 455 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Patrick Leo United States	13	325	192	175	73	64	31	464
Nathan Ing United States	6	165 0.5×	217 1.1×	103 0.6×	80 1.1×	44 0.7×	11	411
Charlie Alexander Hamm Germany	11	421 1.3×	183 1.0×	156 0.9×	69 0.9×	93 1.5×	24	671
Vipul Baxi United States	6	205 0.6×	206 1.1×	63 0.4×	112 1.5×	36 0.6×	16	446
Mireia Crispin‐Ortuzar United Kingdom	10	337 1.0×	121 0.6×	109 0.6×	67 0.9×	92 1.4×	27	471
Charles Maussion France	4	178 0.5×	190 1.0×	74 0.4×	67 0.9×	17 0.3×	12	338
Fahdi Kanavati Japan	11	504 1.6×	500 2.6×	168 1.0×	218 3.0×	59 0.9×	20	794
Behnaz Abdollahi United States	8	207 0.6×	158 0.8×	101 0.6×	143 2.0×	50 0.8×	12	482
Xiangxue Wang United States	13	444 1.4×	339 1.8×	193 1.1×	241 3.3×	58 0.9×	31	759
Zixiao Lu China	10	380 1.2×	265 1.4×	56 0.3×	70 1.0×	65 1.0×	20	602
Isabel Schobert Germany	9	410 1.3×	167 0.9×	99 0.6×	127 1.7×	98 1.5×	18	694

Countries citing papers authored by Patrick Leo

Since Specialization

Citations

This map shows the geographic impact of Patrick Leo'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 Patrick Leo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick Leo more than expected).

Fields of papers citing papers by Patrick Leo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Patrick Leo. 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 Patrick Leo. The network helps show where Patrick Leo may publish in the future.

Co-authorship network of co-authors of Patrick Leo

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick Leo. A scholar is included among the top collaborators of Patrick Leo 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 Patrick Leo. Patrick Leo 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

Corredor, Germán, Lin Li, Patrick Leo, et al.. (2024). An integrated radiology-pathology machine learning classifier for outcome prediction following radical prostatectomy: Preliminary findings. Heliyon. 10(8). e29602–e29602. 4 indexed citations

Leo, Patrick, et al.. (2023). Automatic myeloblast segmentation in acute myeloid leukemia images based on adversarial feature learning. Computer Methods and Programs in Biomedicine. 243. 107852–107852. 8 indexed citations

Braman, Nathaniel, Prateek Prasanna, Kaustav Bera, et al.. (2022). Novel Radiomic Measurements of Tumor-Associated Vasculature Morphology on Clinical Imaging as a Biomarker of Treatment Response in Multiple Cancers. Clinical Cancer Research. 28(20). 4410–4424. 19 indexed citations

Verma, Ruchika, Virginia Hill, Volodymyr Statsevych, et al.. (2022). Stable and Discriminatory Radiomic Features from the Tumor and Its Habitat Associated with Progression-Free Survival in Glioblastoma: A Multi-Institutional Study. American Journal of Neuroradiology. 43(8). 1115–1123. 15 indexed citations

Prasanna, Prateek, Germán Corredor, Cristian Barrera, et al.. (2022). Image analysis reveals molecularly distinct patterns of TILs in NSCLC associated with treatment outcome. npj Precision Oncology. 6(1). 33–33. 32 indexed citations

Leo, Patrick, Vidya Sankar Viswanathan, Andrew Janowczyk, et al.. (2022). Machine Learning to Predict Risk of Relapse Using Cytologic Image Markers in Patients With Acute Myeloid Leukemia Posthematopoietic Cell Transplantation. JCO Clinical Cancer Informatics. 6(6). e2100156–e2100156. 13 indexed citations

Leo, Patrick, Kaustav Bera, Claire W. Michael, et al.. (2022). Automated analysis of computerized morphological features of cell clusters associated with malignancy on bile duct brushing whole slide images. Cancer Medicine. 12(5). 6365–6378. 4 indexed citations

Bhargava, Hersh K., Patrick Leo, Robin Elliott, et al.. (2020). Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients. Clinical Cancer Research. 26(8). 1915–1923. 42 indexed citations

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

10.

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

11.

Khorrami, Mohammadhadi, Kaustav Bera, Patrick Leo, et al.. (2020). Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study. Lung Cancer. 142. 90–97. 34 indexed citations

12.

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

13.

Lu, Cheng, Can Koyuncu, Germán Corredor, et al.. (2020). Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers. Medical Image Analysis. 68. 101903–101903. 41 indexed citations

14.

Koyuncu, Can, Andrew Janowczyk, Cheng Lu, et al.. (2020). Three-dimensional histo-morphometric features from light sheet microscopy images result in improved discrimination of benign from malignant glands in prostate cancer. 15–15. 2 indexed citations

15.

Leo, Patrick, George Lee, Robin Elliott, et al.. (2020). Computer Extracted Features from Initial H&E Tissue Biopsies Predict Disease Progression for Prostate Cancer Patients on Active Surveillance. Cancers. 12(9). 2708–2708. 12 indexed citations

16.

Zhang, Zelin, Patrick Leo, Andrew Janowczyk, et al.. (2020). Computationally derived cytological image markers for predicting risk of relapse in acute myeloid leukemia patients following bone marrow transplantation. 3–3. 3 indexed citations

17.

Li, Lin, Rakesh Shiradkar, Ahmad Algohary, et al.. (2019). Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk score. 142–142. 2 indexed citations

18.

Leo, Patrick, Robin Elliott, Natalie Shih, et al.. (2018). Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study. Scientific Reports. 8(1). 14918–14918. 25 indexed citations

19.

Janowczyk, Andrew, Eswar Shankar, Patrick Leo, et al.. (2018). Combination of nuclear NF-kB/p65 localization and gland morphological features from surgical specimens appears to be predictive of early biochemical recurrence in prostate cancer patients. 7510. 9–9. 2 indexed citations

20.

Leo, Patrick, George Lee, & Anant Madabhushi. (2016). Evaluating stability of histomorphometric features across scanner and staining variations: predicting biochemical recurrence from prostate cancer whole slide images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9791. 97910I–97910I. 7 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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