David F. Steiner

9.6k total citations · 2 hit papers
24 papers, 3.7k citations indexed

About

David F. Steiner is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, David F. Steiner has authored 24 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 11 papers in Radiology, Nuclear Medicine and Imaging and 10 papers in Oncology. Recurrent topics in David F. Steiner's work include Radiomics and Machine Learning in Medical Imaging (10 papers), AI in cancer detection (9 papers) and Colorectal Cancer Screening and Detection (6 papers). David F. Steiner is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (10 papers), AI in cancer detection (9 papers) and Colorectal Cancer Screening and Detection (6 papers). David F. Steiner collaborates with scholars based in United States, Austria and United Kingdom. David F. Steiner's co-authors include Mohammad Shahrokh Esfahani, Chih Long Liu, Chloé B. Steen, Ash A. Alizadeh, Michael S. Khodadoust, Aaron M. Newman, Andrew J. Gentles, Bogdan Luca, Aadel A. Chaudhuri and Maximilian Diehn and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nature Biotechnology and PLoS ONE.

In The Last Decade

David F. Steiner

23 papers receiving 3.6k citations

Hit 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.

Determining cell type abundance and expression from bulk tissues with digital cytometry

2019 2.4k citations Aaron M. Newman, Chloé B. Steen et al. Nature Biotechnology profile →
Impact of Deep Learning Assistance on the Histopathologic Review of Lymph Nodes for Metastatic Breast Cancer

2018 308 citations David F. Steiner, Yun Liu et al. profile →

Peers

Countries citing papers authored by David F. Steiner

Since Specialization

Citations

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

Fields of papers citing papers by David F. Steiner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David F. Steiner. 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 David F. Steiner. The network helps show where David F. Steiner may publish in the future.

Co-authorship network of co-authors of David F. Steiner

This figure shows the co-authorship network connecting the top 25 collaborators of David F. Steiner. A scholar is included among the top collaborators of David F. Steiner 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 David F. Steiner. David F. Steiner 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	PolyPath: Adapting a Large Multimodal Model for Multislide Pathology Report Generation 2025 ·Modern Pathology ·(unknown), Lin Yang, (unknown), (unknown), Yossi Matias, Avinatan Hassidim, Greg S. Corrado, Dale R. Webster, Shravya Shetty, (unknown), Y. Liu, (unknown), Ellery Wulczyn, David F. Steiner	0
2	Performance of machine learning models for predicting high-severity symptoms in multiple sclerosis 2025 ·Scientific Reports ·Subhrajit Roy, Diana Mincu, Lev Proleev, (unknown), Jennifer Graves, David F. Steiner, (unknown), Katherine Heller	1
3	Converging deep learning and human-observed tumor-adipocyte interaction as a biomarker in colorectal cancer 2024 ·SHILAP Revista de lepidopterología ·(unknown), Bianca Grosser, David F. Steiner, Veselin Grozdanov, Ellery Wulczyn, Vincenzo L’Imperio, Markus Plass, Heimo Müller, Kurt Zatloukal, (unknown), Jakob Nikolas Kather, Bruno Märkl	7
4	Clinical-Grade Validation of an Autofluorescence Virtual Staining System With Human Experts and a Deep Learning System for Prostate Cancer 2024 ·Modern Pathology ·Pok Fai Wong, (unknown), (unknown), (unknown), Charles Santori, (unknown), Andrew Homyk, Kunal Nagpal, (unknown), Ellery Wulczyn, Tadayuki Yoshitake, (unknown), David F. Steiner, Sudha Rao, Po-Hsuan Cameron Chen, (unknown), (unknown), Peter Cimermančič	4
5	Predicting lymph node metastasis from primary tumor histology and clinicopathologic factors in colorectal cancer using deep learning 2023 ·SHILAP Revista de lepidopterología ·Justin D. Krogue, Shekoofeh Azizi, Fraser Elisabeth Tan, (unknown), Trissia Brown, Markus Plass, Robert Reihs, Heimo Müller, Kurt Zatloukal, (unknown), Greg S. Corrado, Lily H. Peng, Craig H. Mermel, Yun Liu, Po-Hsuan Cameron Chen, Saurabh Gombar, Thomas J. Montine, Jeanne Shen, David F. Steiner, Ellery Wulczyn	12
6	Pathologist Validation of a Machine Learning–Derived Feature for Colon Cancer Risk Stratification 2023 ·JAMA Network Open ·Vincenzo L’Imperio, Ellery Wulczyn, Markus Plass, Heimo Müller, Nicolò Tamini, Luca Gianotti, Nicola Zucchini, Robert Reihs, Greg S. Corrado, Dale R. Webster, Lily H. Peng, Po-Hsuan Cameron Chen, Marialuisa Lavitrano, Yun Liu, David F. Steiner, Kurt Zatloukal, Fabio Pagni	31
7	A Multiplex SNaPshot Assay is a Rapid and Cost-Effective Method for Detecting POLE Exonuclease Domain Mutations in Endometrial Carcinoma 2021 ·International Journal of Gynecological Pathology ·Kelly A. Devereaux, David F. Steiner, (unknown), Adam J. Gomez, C. Blake Gilks, Teri A. Longacre, James L. Zehnder, Brooke E. Howitt, Carlos J. Suarez	18
8	Prospective molecular classification of endometrial carcinomas: institutional implementation, practice, and clinical experience 2021 ·Modern Pathology ·Kelly A. Devereaux, (unknown), Jennifer Pors, David F. Steiner, (unknown), Vivek Charu, Carlos J. Suarez, Malte Renz, Elisabeth Diver, Amer Karam, Babak Litkouhi, Oliver Dorigo, Elizabeth Kidd, Eric Yang, Ann K. Folkins, Teri A. Longacre, Brooke E. Howitt	37
9	Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images 2021 ·Scientific Reports ·Apaar Sadhwani, (unknown), Ali Behrooz, Trissia Brown, (unknown), (unknown), (unknown), (unknown), Fraser Elisabeth Tan, (unknown), Ellery Wulczyn, Eunhee S. Yi, Craig H. Mermel, Debra Hanks, Po-Hsuan Cameron Chen, Kimary Kulig, Cory Batenchuk, David F. Steiner, Peter Cimermančič	34
10	Determining breast cancer biomarker status and associated morphological features using deep learning 2021 ·Communications Medicine ·Paul Gamble, Ronnachai Jaroensri, Hongwu Wang, Fraser Elisabeth Tan, Melissa Moran, Trissia Brown, (unknown), Emad A. Rakha, Michael S. Toss, David J. Dabbs, Peter Regitnig, Niels Olson, (unknown), (unknown), Greg S. Corrado, Lily H. Peng, Yun Liu, Craig H. Mermel, David F. Steiner, Po-Hsuan Cameron Chen	86
11	Onboarding Materials as Cross-functional Boundary Objects for Developing AI Assistants 2021 ·Carrie J. Cai, Samantha Winter, David F. Steiner, Lauren Wilcox, Michael Terry	25
12	Closing the translation gap: AI applications in digital pathology 2020 ·Biochimica et Biophysica Acta (BBA) - Reviews on Cancer ·David F. Steiner, Po-Hsuan Cameron Chen, Craig H. Mermel	51
13	Deep learning-based survival prediction for multiple cancer types using histopathology images 2020 ·PLoS ONE ·Ellery Wulczyn, David F. Steiner, Zhaoyang Xu, Apaar Sadhwani, Hongwu Wang, (unknown), Craig H. Mermel, Po-Hsuan Cameron Chen, Yun Liu, Martin C. Stumpe	159
14	Morphological, immunophenotypical and molecular features of hypermutation in colorectal carcinomas with mutations in DNA polymerase ε (POLE) 2019 ·Histopathology ·Erna Forgó, Adam J. Gomez, David F. Steiner, James L. Zehnder, Teri A. Longacre	16
15	Determining cell type abundance and expression from bulk tissues with digital cytometry breakdown → 2019 ·Nature Biotechnology ·Aaron M. Newman, Chloé B. Steen, Chih Long Liu, Andrew J. Gentles, Aadel A. Chaudhuri, Florian Scherer, Michael S. Khodadoust, Mohammad Shahrokh Esfahani, Bogdan Luca, David F. Steiner, Maximilian Diehn, Ash A. Alizadeh	2365
16	Pharma-Oncogenomics in the Era of Personal Genomics: A Quick Guide to Online Resources and Tools 2019 ·Advances in experimental medicine and biology ·Rohan P. Joshi, David F. Steiner, Eric Q. Konnick, Carlos J. Suarez	3
17	Complete and Prolonged Response to Immune Checkpoint Blockade in POLE-Mutated Colorectal Cancer 2019 ·JCO Precision Oncology ·(unknown), David F. Steiner, (unknown), Adam J. Gomez, James L. Zehnder, Gilbert Chu, Carlos J. Suarez	28
18	High-throughput Sequencing of Subcutaneous Panniculitis-like T-Cell Lymphoma Reveals Candidate Pathogenic Mutations 2019 ·Applied immunohistochemistry & molecular morphology ·Sebastian Fernandez‐Pol, Helio A. Costa, David F. Steiner, Lisa Ma, Jason D. Merker, Youn H. Kim, Daniel A. Arber, Jinah Kim	7
19	Coexistence of BRAF V600E and TERT Promoter Mutations in Low-grade Serous Carcinoma of Ovary Recurring as Carcinosarcoma in a Lymph Node: Report of a Case 2018 ·International Journal of Gynecological Pathology ·Mahkam Tavallaee, David F. Steiner, James L. Zehnder, Ann K. Folkins, Amer Karam	3
20	A system for consistency preserving belief change 2006 ·Bern Open Repository and Information System (University of Bern) ·David F. Steiner	3

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.

Explore authors with similar magnitude of impact