Daniel L. Rubin

25.8k total citations · 6 hit papers
366 papers, 15.9k citations indexed

About

Daniel L. Rubin is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Daniel L. Rubin has authored 366 papers receiving a total of 15.9k indexed citations (citations by other indexed papers that have themselves been cited), including 199 papers in Radiology, Nuclear Medicine and Imaging, 148 papers in Artificial Intelligence and 109 papers in Molecular Biology. Recurrent topics in Daniel L. Rubin's work include Radiomics and Machine Learning in Medical Imaging (111 papers), Biomedical Text Mining and Ontologies (91 papers) and AI in cancer detection (78 papers). Daniel L. Rubin is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (111 papers), Biomedical Text Mining and Ontologies (91 papers) and AI in cancer detection (78 papers). Daniel L. Rubin collaborates with scholars based in United States, China and Canada. Daniel L. Rubin's co-authors include Assaf Hoogi, Sandy Napel, Luís de Sisternes, Alfiia Galimzianova, Gerald J. Berry, Russ B. Altman, Mark A. Musen, Francisco Javier Giménez Fuentes‐Guerra, Bradley J. Erickson and Christopher Ré and has published in prestigious journals such as New England Journal of Medicine, Nucleic Acids Research and Nature Communications.

In The Last Decade

Daniel L. Rubin

356 papers receiving 15.5k 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.

Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions

2017 722 citations Alfiia Galimzianova, Assaf Hoogi et al. profile →
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features

2016 680 citations Daniel L. Rubin et al. Nature Communications profile →
BioPortal: ontologies and integrated data resources at the click of a mouse

2009 556 citations Daniel L. Rubin, Margaret‐Anne Storey et al. profile →
Preparing Medical Imaging Data for Machine Learning

2020 553 citations Daniel L. Rubin et al. profile →
A curated mammography data set for use in computer-aided detection and diagnosis research

2017 493 citations Francisco Javier Giménez Fuentes‐Guerra, Assaf Hoogi et al. profile →
Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging

2023 89 citations Liangqiong Qu, Daniel L. Rubin et al. IEEE Transactions on Medical Imaging profile →

Peers

Countries citing papers authored by Daniel L. Rubin

Since Specialization

Citations

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

Fields of papers citing papers by Daniel L. Rubin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel L. Rubin. 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 Daniel L. Rubin. The network helps show where Daniel L. Rubin may publish in the future.

Co-authorship network of co-authors of Daniel L. Rubin

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel L. Rubin. A scholar is included among the top collaborators of Daniel L. Rubin 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 Daniel L. Rubin. Daniel L. Rubin 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	Automated Extraction of Patient-Centered Outcomes After Breast Cancer Treatment: An Open-Source Large Language Model–Based Toolkit 2024 ·JCO Clinical Cancer Informatics ·(unknown), (unknown), Allison W. Kurian, Kevin C. Ward, Theresa H.M. Keegan, Daniel L. Rubin, Imon Banerjee	6
2	PlexusNet: A neural network architectural concept for medical image classification 2023 ·Computers in Biology and Medicine ·Okyaz Eminağa, Mahmoud Abbas, Jeanne Shen, (unknown), James D. Brooks, Joseph C. Liao, Daniel L. Rubin	15
3	AI Transformers for Radiation Dose Reduction in Serial Whole-Body PET Scans 2023 ·Radiology Artificial Intelligence ·(unknown), Liangqiong Qu, Natasha Sheybani, (unknown), (unknown), K. Elizabeth Hawk, Ashok J. Theruvath, Sergios Gatidis, Xue‐Rong Xiao, Allison Pribnow, Daniel L. Rubin, Heike E. Daldrup‐Link	9
4	Machine Learning–Enabled Multimodal Fusion of Intra-Atrial and Body Surface Signals in Prediction of Atrial Fibrillation Ablation Outcomes 2022 ·Circulation Arrhythmia and Electrophysiology ·Siyi Tang, Orod Razeghi, (unknown), Mahmood Alhusseini, Muhammad Fazal, Albert J. Rogers, (unknown), Paul Clopton, Paul J. Wang, Daniel L. Rubin, Sanjiv M. Narayan, Tina Baykaner	45
5	Toward Reduction in False-Positive Thyroid Nodule Biopsies with a Deep Learning–based Risk Stratification System Using US Cine-Clip Images 2022 ·Radiology Artificial Intelligence ·Rikiya Yamashita, (unknown), Minhaj Nur Alam, Alfiia Galimzianova, (unknown), (unknown), (unknown), Andrew L. Wentland, (unknown), Daniel Goff, (unknown), Natasha Sheybani, Hersh Sagreiya, Daniel L. Rubin, Terry S. Desser	11
6	Data Sharing of Imaging in an Evolving Health Care World: Report of the ACR Data Sharing Workgroup, Part 1: Data Ethics of Privacy, Consent, and Anonymization 2021 ·Journal of the American College of Radiology ·Juan Batlle, Keith J. Dreyer, Bibb Allen, Tessa S. Cook, Christopher J. Roth, Andrea Borondy Kitts, (unknown), Carol C. Wu, (unknown), (unknown), Adam Prater, Daniel L. Rubin, Safwan S. Halabi, (unknown), (unknown), Laura P. Coombs, Christoph Wald	18
7	Artificial intelligence enables whole-body positron emission tomography scans with minimal radiation exposure 2021 ·European Journal of Nuclear Medicine and Molecular Imaging ·(unknown), Lucia Baratto, K. Elizabeth Hawk, Ashok J. Theruvath, Allison Pribnow, Avnesh S. Thakor, Sergios Gatidis, Rong Lü, Santosh Gummidipundi, (unknown), Daniel L. Rubin, Heike E. Daldrup‐Link	58
8	AI-based structure-function correlation in age-related macular degeneration 2021 ·Eye ·Leon von der Emde, Maximilian Pfau, Frank G. Holz, Monika Fleckenstein, Karsten Kortuem, Pearse A. Keane, Daniel L. Rubin, Steffen Schmitz-Valckenberg	15
9	Learning Domain-Agnostic Visual Representation for Computational Pathology Using Medically-Irrelevant Style Transfer Augmentation 2021 ·IEEE Transactions on Medical Imaging ·Rikiya Yamashita, Jin Long, (unknown), Jeanne Shen, Daniel L. Rubin	40
10	Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk 2020 ·Nature Communications ·Weiva Sieh, Joseph H. Rothstein, Robert J. Klein, Stacey Alexeeff, Lori C. Sakoda, Eric Jorgenson, Russell B. McBride, Rebecca E. Graff, Valerie McGuire, Ninah Achacoso, (unknown), Rhea Liang, Jafi A. Lipson, Daniel L. Rubin, Martin J. Yaffe, Douglas F. Easton, Catherine Schaefer, Neil Risch, Alice S. Whittemore, Laurel A. Habel	23
11	A Probabilistic Model to Support Radiologists’ Classification Decisions in Mammography Practice 2019 ·Medical Decision Making ·(unknown), Francisco Javier Giménez Fuentes‐Guerra, Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter	4
12	DALS: Deep Active Lesion Segmentation 2019 ·arXiv (Cornell University) ·Ali Hatamizadeh, Assaf Hoogi, (unknown), (unknown), (unknown), Daniel L. Rubin, Demetri Terzopoulos	0
13	Deep Learning in Neuroradiology 2018 ·American Journal of Neuroradiology ·Greg Zaharchuk, Enhao Gong, Max Wintermark, Daniel L. Rubin, Curtis P. Langlotz	215
14	Age at Menarche and Late Adolescent Adiposity Associated with Mammographic Density on Processed Digital Mammograms in 24,840 Women 2017 ·Cancer Epidemiology Biomarkers & Prevention ·Stacey Alexeeff, (unknown), Jafi A. Lipson, Ninah Achacoso, Joseph H. Rothstein, Martin J. Yaffe, Rhea Liang, (unknown), Valerie McGuire, Alice S. Whittemore, Daniel L. Rubin, Weiva Sieh, Laurel A. Habel	18
15	Toward Automated Pre-Biopsy Thyroid Cancer Risk Estimation in Ultrasound. 2017 ·PubMed Central ·Alfiia Galimzianova, Sean M. Siebert, Aya Kamaya, Terry S. Desser, Daniel L. Rubin	2
16	Opening the Black Box: Visualization of Deep Neural Network for Detection of Disease in Retinal Fundus Photographs 2017 ·Investigative Ophthalmology & Visual Science ·Laura C. Huang, Caroline Yu, Robert A. Kleinman, (unknown), Ryan Smith, Carson Lam, Darvin Yi, Daniel L. Rubin	0
17	Computational Identification of Tumor Anatomic Location Associated with Survival in 2 Large Cohorts of Human Primary Glioblastomas 2016 ·American Journal of Neuroradiology ·(unknown), Achal S. Achrol, Lex A. Mitchell, (unknown), Joshua Loya, (unknown), Abdullah H. Feroze, Erick M. Westbroek, Kristen W. Yeom, Joshua M. Stuart, Daniel T. Chang, (unknown), Daniel L. Rubin	27
18	Prognostic PET 18F-FDG Uptake Imaging Features Are Associated with Major Oncogenomic Alterations in Patients with Resected Non–Small Cell Lung Cancer 2012 ·Cancer Research ·Viswam S. Nair, Olivier Gevaert, Guido Davidzon, Sandy Napel, Edward E. Graves, Chuong D. Hoang, Joseph B. Shrager, Andrew Quon, Daniel L. Rubin, Sylvia K. Plevritis	103
19	Web service access to semantic web ontologies for data annotation. 2008 ·PubMed ·(unknown), José L. V. Mejino, Landon T Detwiler, Daniel L. Rubin, James F. Brinkley	2
20	The National Center for Biomedical Ontology: Advancing Biomedicine through Structured \nOrganization of Scientific Knowledge 2006 ·eScholarship (California Digital Library) ·Daniel L. Rubin, Suzanna Lewis, Chris Mungall, Sima Misra, Monte Westerfield, Michael Ashburner, Ida Sim, Christopher G. Chute, (unknown), Margaret‐Anne Storey, Barry Smith, (unknown), Natalya F. Noy, Mark A. Musen	110

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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