Samuel G. Finlayson

3.3k total citations · 1 hit paper
22 papers, 1.1k citations indexed

About

Samuel G. Finlayson is a scholar working on Artificial Intelligence, Health Informatics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Samuel G. Finlayson has authored 22 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 7 papers in Health Informatics and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Samuel G. Finlayson's work include Artificial Intelligence in Healthcare and Education (7 papers), Machine Learning in Healthcare (5 papers) and AI in cancer detection (3 papers). Samuel G. Finlayson is often cited by papers focused on Artificial Intelligence in Healthcare and Education (7 papers), Machine Learning in Healthcare (5 papers) and AI in cancer detection (3 papers). Samuel G. Finlayson collaborates with scholars based in United States, United Kingdom and France. Samuel G. Finlayson's co-authors include Isaac S. Kohane, Andrew L. Beam, Joichi Ito, Jonathan Zittrain, Nigam H. Shah, Paea LePendu, Brett K. Beaulieu‐Jones, Vinay Prasad, Kun‐Hsing Yu and Russ B. Altman and has published in prestigious journals such as Science, Nature Communications and PLoS ONE.

In The Last Decade

Samuel G. Finlayson

20 papers receiving 1.1k citations

Hit Papers

align trajectories sort by overperformance

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.

Adversarial attacks on medical machine learning

2019 525 citations Samuel G. Finlayson, Joichi Ito et al. Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Samuel G. Finlayson United States	13	470	262	212	189	91	22	1.1k
Wenqi Shi United States	15	225 0.5×	340 1.3×	118 0.6×	127 0.7×	48 0.5×	79	954
Brett K. Beaulieu‐Jones United States	16	624 1.3×	191 0.7×	266 1.3×	167 0.9×	84 0.9×	33	1.4k
Faraz S. Ahmad United States	26	260 0.6×	165 0.6×	164 0.8×	224 1.2×	79 0.9×	120	2.3k
Alexis B. Carter United States	20	627 1.3×	333 1.3×	57 0.3×	402 2.1×	194 2.1×	50	1.9k
Emma Chen United States	7	456 1.0×	414 1.6×	593 2.8×	88 0.5×	133 1.5×	13	1.4k
Rahul Paul United States	18	402 0.9×	553 2.1×	361 1.7×	69 0.4×	85 0.9×	55	1.4k
Nhan Do United States	18	207 0.4×	201 0.8×	88 0.4×	140 0.7×	60 0.7×	85	1.2k
Tu Bao Ho Japan	17	543 1.2×	129 0.5×	122 0.6×	274 1.4×	56 0.6×	82	1.6k
Beau Norgeot United States	9	300 0.6×	186 0.7×	215 1.0×	52 0.3×	55 0.6×	17	762

Countries citing papers authored by Samuel G. Finlayson

Since Specialization

Citations

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

Fields of papers citing papers by Samuel G. Finlayson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Samuel G. Finlayson. 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 Samuel G. Finlayson. The network helps show where Samuel G. Finlayson may publish in the future.

Co-authorship network of co-authors of Samuel G. Finlayson

This figure shows the co-authorship network connecting the top 25 collaborators of Samuel G. Finlayson. A scholar is included among the top collaborators of Samuel G. Finlayson 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 Samuel G. Finlayson. Samuel G. Finlayson 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

Finlayson, Samuel G., et al.. (2025). Accuracy of Artificial Intelligence vs Professionally Translated Discharge Instructions. JAMA Network Open. 8(9). e2532312–e2532312.

Gleeson, Joseph G., Laurence Mignon, Winston X. Yan, et al.. (2024). A framework for N-of-1 trials of individualized gene-targeted therapies for genetic diseases. Nature Communications. 15(1). 9802–9802. 7 indexed citations

Levine, David M., Rudraksh Tuwani, Benjamin Kompa, et al.. (2024). The diagnostic and triage accuracy of the GPT-3 artificial intelligence model: an observational study. The Lancet Digital Health. 6(8). e555–e561. 39 indexed citations

Tobias, Joseph, Emmanuel A. Ameh, Samuel G. Finlayson, et al.. (2024). Evaluating Global Surgery Partnerships From Low and Middle Income Country Perspectives. Journal of Surgical Research. 296. 681–688.

Alsentzer, Emily, et al.. (2023). Simulation of undiagnosed patients with novel genetic conditions. Nature Communications. 14(1). 6403–6403. 4 indexed citations

Finlayson, Samuel G., Andrew L. Beam, & Maarten van Smeden. (2023). Machine Learning and Statistics in Clinical Research Articles—Moving Past the False Dichotomy. JAMA Pediatrics. 177(5). 448–448. 13 indexed citations

Daneshjou, Roxana, Steven E. Brenner, Jonathan H. Chen, et al.. (2022). Precision Medicine: Using Artificial Intelligence to Improve Diagnostics and Healthcare.. PubMed. 27. 223–230. 3 indexed citations

Korot, Edward, Daniel Ferraz, Siegfried K. Wagner, et al.. (2021). Code-free deep learning for multi-modality medical image classification. Nature Machine Intelligence. 3(4). 288–298. 115 indexed citations

Daneshjou, Roxana, Steven E. Brenner, Jonathan H. Chen, et al.. (2021). Precision Medicine: Using Artificial Intelligence to Improve Diagnostics and Healthcare. 223–230. 3 indexed citations

10.

Alsentzer, Emily, Samuel G. Finlayson, Michelle M. Li, & Marinka Žitnik. (2020). Subgraph Neural Networks. Neural Information Processing Systems. 33. 8017–8029. 5 indexed citations

11.

Lipnick, Scott, Denis Agniel, Rahul Aggarwal, et al.. (2019). Systemic nature of spinal muscular atrophy revealed by studying insurance claims. PLoS ONE. 14(3). e0213680–e0213680. 53 indexed citations

12.

Finlayson, Samuel G., et al.. (2019). Adversarial attacks on medical machine learning. Science. 363(6433). 1287–1289. 525 indexed citations breakdown →

13.

Beaulieu‐Jones, Brett K., Samuel G. Finlayson, William Yuan, et al.. (2019). Examining the Use of Real‐World Evidence in the Regulatory Process. Clinical Pharmacology & Therapeutics. 107(4). 843–852. 105 indexed citations

14.

Finlayson, Samuel G., Hyunkwang Lee, Isaac S. Kohane, & Luke Oakden‐Rayner. (2018). Towards generative adversarial networks as a new paradigm for radiology education. arXiv (Cornell University). 1 indexed citations

15.

Gurry, Thomas, Paul H. Dannenberg, Samuel G. Finlayson, et al.. (2018). Predictability and persistence of prebiotic dietary supplementation in a healthy human cohort. Scientific Reports. 8(1). 12699–12699. 34 indexed citations

16.

Weiss, Hannah, Ziad C. Sifri, Sanjay Krishnaswami, et al.. (2018). Are we meeting ACGME core competencies? A systematic review of literature on international surgical rotations. The American Journal of Surgery. 216(4). 782–786. 17 indexed citations

17.

Tu, Xiaoguang, Mei Xie, Jingjing Gao, et al.. (2017). Automatic Categorization and Scoring of Solid, Part-Solid and Non-Solid Pulmonary Nodules in CT Images with Convolutional Neural Network. Scientific Reports. 7(1). 8533–8533. 30 indexed citations

18.

Finlayson, Samuel G., Mia Levy, Sunil Reddy, & Daniel L. Rubin. (2016). Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data. Journal of Biomedical Informatics. 60. 104–113. 15 indexed citations

19.

Wells, Katie, Raymond R. Price, Samuel G. Finlayson, & Catherine R. deVries. (2014). Fundamentals for establishing and maintaining an academic centre for global surgery: the University of Utah experience. The Lancet Global Health. 2. S47–S47. 1 indexed citations

20.

Finlayson, Samuel G., Paea LePendu, & Nigam H. Shah. (2014). Building the graph of medicine from millions of clinical narratives. Scientific Data. 1(1). 140032–140032. 61 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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