Michael D. Feldman

52.8k total citations · 8 hit papers
276 papers, 15.3k citations indexed

About

Michael D. Feldman is a scholar working on Oncology, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Michael D. Feldman has authored 276 papers receiving a total of 15.3k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Oncology, 64 papers in Artificial Intelligence and 60 papers in Molecular Biology. Recurrent topics in Michael D. Feldman's work include AI in cancer detection (62 papers), Radiomics and Machine Learning in Medical Imaging (38 papers) and Medical Image Segmentation Techniques (29 papers). Michael D. Feldman is often cited by papers focused on AI in cancer detection (62 papers), Radiomics and Machine Learning in Medical Imaging (38 papers) and Medical Image Segmentation Techniques (29 papers). Michael D. Feldman collaborates with scholars based in United States, Switzerland and China. Michael D. Feldman's co-authors include Anant Madabhushi, John Tomaszewski, Natalie Shih, Scott Doyle, Shridar Ganesan, Ajay Basavanhally, Hannah Gilmore, Priti Lal, Shannon C. Agner and George Coukos and has published in prestigious journals such as Cell, Circulation and Journal of Clinical Investigation.

In The Last Decade

Michael D. Feldman

272 papers receiving 15.0k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

BRAF and RAS mutations in human lung cancer and melanoma.

2002 841 citations Michael D. Feldman et al. PubMed profile →
Tumor Interferon Signaling Regulates a Multigenic Resistance Program to Immune Checkpoint Blockade

2016 804 citations Lynn M. Schuchter, Michael D. Feldman et al. profile →
Tumor endothelium FasL establishes a selective immune barrier promoting tolerance in tumors

2014 770 citations Ian S. Hagemann, Priti Lal et al. profile →
Tumor-associated neutrophils stimulate T cell responses in early-stage human lung cancer

2014 495 citations Evgeniy Eruslanov, Michael D. Feldman et al. profile →
Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks

2014 377 citations Michael D. Feldman, Natalie Shih et al. profile →
Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

2017 349 citations Michael D. Feldman, Natalie Shih et al. profile →
Randomized Phase II Trial of Nivolumab Versus Nivolumab and Ipilimumab for Recurrent or Persistent Ovarian Cancer: An NRG Oncology Study

2020 224 citations Dmitriy Zamarin, Robert A. Burger et al. Journal of Clinical Oncology profile →
Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology

2024 73 citations Daiwei Zhang, Amelia Schroeder et al. Nature Biotechnology profile →

Peers

Countries citing papers authored by Michael D. Feldman

Since Specialization

Citations

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

Fields of papers citing papers by Michael D. Feldman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael D. Feldman. 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 Michael D. Feldman. The network helps show where Michael D. Feldman may publish in the future.

Co-authorship network of co-authors of Michael D. Feldman

This figure shows the co-authorship network connecting the top 25 collaborators of Michael D. Feldman. A scholar is included among the top collaborators of Michael D. Feldman 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 Michael D. Feldman. Michael D. Feldman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology breakdown → 2024 ·Nature Biotechnology ·Daiwei Zhang, Amelia Schroeder, Hanying Yan, (unknown), Jian Hu, Michelle Y. Y. Lee, (unknown), Katalin Suszták, Xiaowei Xu, Michael D. Feldman, Edward B. Lee, Emma E. Furth, Linghua Wang, Mingyao Li	73
2	Protein Kinase C Alpha is a Central Node for Tumorigenic Transcriptional Networks in Human Prostate Cancer 2022 ·Cancer Research Communications ·Mariana Cooke, Xuyao Zhang, Suli Zhang, Evgeniy Eruslanov, Priti Lal, (unknown), Michael D. Feldman, Martı́n C. Abba, Marcelo G. Kazanietz	7
3	PTEN Loss and BRCA1 Promoter Hypermethylation Negatively Predict for Immunogenicity in BRCA-Deficient Ovarian Cancer 2022 ·JCO Precision Oncology ·Adam Kraya, Kara N. Maxwell, Monika A. Eiva, Bradley Wubbenhorst, John Pluta, Michael D. Feldman, Anupma Nayak, Daniel J. Powell, Susan M. Domchek, Robert H. Vonderheide, Katherine L. Nathanson	9
4	Comparative Analysis of Emerging B.1.1.7+E484K SARS-CoV-2 Isolates 2021 ·Open Forum Infectious Diseases ·Ahmed M. Moustafa, (unknown), (unknown), (unknown), Susan Coffin, (unknown), J.K. Everett, Shantan Reddy, (unknown), (unknown), Michael D. Feldman, Kyle G. Rodino, Frederic D. Bushman, Rebecca M. Harris, (unknown), Paul J. Planet	11
5	A Natural Language Processing–Assisted Extraction System for Gleason Scores: Development and Usability Study 2021 ·JMIR Cancer ·Shun Yu, Anh N. Le, Emily Feld, Emily Schriver, Peter Gabriel, Abigail Doucette, Vivek Narayan, Michael D. Feldman, Lauren E. Schwartz, Kara N. Maxwell, Danielle L. Mowery	7
6	Computationally Derived Image Signature of Stromal Morphology Is Prognostic of Prostate Cancer Recurrence Following Prostatectomy in African American Patients 2020 ·Clinical Cancer Research ·Hersh K. Bhargava, Patrick Leo, Robin Elliott, Andrew Janowczyk, Jon Whitney, Sanjay Gupta, Pingfu Fu, Kosj Yamoah, Francesca Khani, Brian D. Robinson, Timothy R. Rebbeck, Michael D. Feldman, Priti Lal, Anant Madabhushi	42
7	Randomized Phase II Trial of Nivolumab Versus Nivolumab and Ipilimumab for Recurrent or Persistent Ovarian Cancer: An NRG Oncology Study breakdown → 2020 ·Journal of Clinical Oncology ·Dmitriy Zamarin, Robert A. Burger, Michael W. Sill, Daniel J. Powell, Heather A. Lankes, Michael D. Feldman, Oliver Zivanovic, Camille C. Gunderson, Emily Ko, Cara Mathews, Sudarshan Sharma, Andrea R. Hagemann, Samir N. Khleif, Carol Aghajanian	224
8	Changes in CT Radiomic Features Associated with Lymphocyte Distribution Predict Overall Survival and Response to Immunotherapy in Non–Small Cell Lung Cancer 2019 ·Cancer Immunology Research ·Mohammadhadi Khorrami, Prateek Prasanna, Amit Gupta, Pradnya D. Patil, Priya Velu, Rajat Thawani, Germán Corredor, Mehdi Alilou, Kaustav Bera, Pingfu Fu, Michael D. Feldman, Vamsidhar Velcheti, Anant Madabhushi	200
9	Genomic Signatures Predict the Immunogenicity of BRCA-Deficient Breast Cancer 2019 ·Clinical Cancer Research ·Adam Kraya, Kara N. Maxwell, Bradley Wubbenhorst, Brandon M. Wenz, John Pluta, Andrew J. Rech, Liza M. Dorfman, (unknown), (unknown), Nandita Mitra, Jennifer J.D. Morrissette, Michael D. Feldman, Anupma Nayak, Susan M. Domchek, Robert H. Vonderheide, Katherine L. Nathanson	57
10	Combination Paclitaxel and Palbociclib: Results of a Phase I Trial in Advanced Breast Cancer 2019 ·Clinical Cancer Research ·Amy S. Clark, Nicholas P. McAndrew, Andrea B. Troxel, Michael D. Feldman, Priti Lal, Mark Rosen, (unknown), Colleen Redlinger, Maryann Gallagher, Angela R. Bradbury, Susan M. Domchek, Kevin R. Fox, Peter J. O’Dwyer, Angela DeMichele	35
11	Imaging Phenotypes of Breast Cancer Heterogeneity in Preoperative Breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) Scans Predict 10-Year Recurrence 2019 ·Clinical Cancer Research ·Rhea Chitalia, (unknown), Elizabeth S. McDonald, Lauren Pantalone, Eric A. Cohen, Aimilia Gastounioti, Michael D. Feldman, Mitchell D. Schnall, Emily F. Conant, Despina Kontos	54
12	A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue 2018 ·PLoS ONE ·Jeffrey Nirschl, Andrew Janowczyk, Eliot Peyster, Renee Frank, Kenneth B. Margulies, Michael D. Feldman, Anant Madabhushi	74
13	Overcoming the Immunosuppressive Tumor Microenvironment of Hodgkin Lymphoma Using Chimeric Antigen Receptor T Cells 2017 ·Cancer Discovery ·Marco Ruella, Michael Klichinsky, Saad S. Kenderian, Olga Shestova, Amy Ziober, (unknown), Michael D. Feldman, Mariusz A. Wasik, Carl H. June, Saar Gill	153
14	Generation of Potent T-cell Immunotherapy for Cancer Using DAP12-Based, Multichain, Chimeric Immunoreceptors 2015 ·Cancer Immunology Research ·Enxiu Wang, Liang-Chuan Wang, Ching‐Yi Tsai, Vijay Bhoj, (unknown), Edmund K. Moon, Kheng Newick, Jing Sun, Albert Lo, Timothy Baradet, Michael D. Feldman, David M. Barrett, Ellen Puré, Steven Albelda, Michael C. Milone	91
15	The Ovarian Cancer Chemokine Landscape Is Conducive to Homing of Vaccine-Primed and CD3/CD28–Costimulated T Cells Prepared for Adoptive Therapy 2015 ·Clinical Cancer Research ·Emese Zsíros, Priyanka Duttagupta, Denarda Dangaj Laniti, Hongzhe Li, Renee Frank, Thomas Garrabrant, Ian S. Hagemann, Bruce L. Levine, Carl H. June, Lin Zhang, Ena Wang, Francesco M. Marincola, Davide Bedognetti, Daniel J. Powell, János L. Tanyi, Michael D. Feldman, Lana E. Kandalaft, George Coukos	48
16	CDK 4/6 Inhibitor Palbociclib (PD0332991) in Rb+ Advanced Breast Cancer: Phase II Activity, Safety, and Predictive Biomarker Assessment 2014 ·Clinical Cancer Research ·Angela DeMichele, Amy S. Clark, Kay See Tan, Daniel F. Heitjan, Kristi Gramlich, Maryann Gallagher, Priti Lal, Michael D. Feldman, Paul J. Zhang, Christopher Colameco, David A. Lewis, Melissa Langer, Noah Goodman, Susan M. Domchek, Keerthi Gogineni, Mark Rosen, Kevin R. Fox, Peter J. O’Dwyer	280
17	Image microarrays (IMA): Digital pathology’s missing tool 2011 ·Journal of Pathology Informatics ·Jason Hipp, Jerome Cheng, Liron Pantanowitz, Stephen M. Hewitt, Yukako Yagi, James Monaco, Anant Madabhushi, Jaime Rodriguez‐Canales, Jeffrey C. Hanson, Sinchita Roy‐Chowdhuri, Armando Filie, Michael D. Feldman, John E. Tomaszewski, Natalie Shih, (unknown), Giuseppe Giaccone, Michael R. Emmert‐Buck, Ulysses J. Balis	8
18	Telomerase-Specific T-Cell Immunity in Breast Cancer: Effect of Vaccination on Tumor Immunosurveillance 2007 ·Cancer Research ·Susan M. Domchek, Adri Recio, Rosemarie Mick, Carolyn E. Clark, Erica L. Carpenter, Kevin R. Fox, Angela DeMichele, Lynn M. Schuchter, Michael S. Leibowitz, (unknown), Barbara A. Vance, Gregory L. Beatty, Elizabeth Veloso, Michael D. Feldman, Robert H. Vonderheide	75
19	Interleukin-12 inhibits angiogenesis and growth of transplanted but not in situ mouse mammary tumor virus-induced mammary carcinomas. 2002 ·PubMed ·James Lee, David C. Kim, Michael S. Gee, Helen Saunders, Chandra M. Sehgal, Michael D. Feldman, Susan R. Ross, William M. F. Lee	28
20	The use of microfabricated probes to penetrate the internal elastic lamina and intimal hyperplasia 1999 ·(unknown), Chun‐Chieh Wu, David A. Vorp, Melvin L. Reed, Leo Weiss, Harvey S. Borovetz, Simon C. Watkins, Michael D. Feldman	1

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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