RS

Rory Sayres

0000-0002-8269-5779

cs.LGArtificial IntelligenceDeep Learningcs.CVcs.CLstat.MLBrain MappingBreast Neoplasmscs.AIcs.CY

On Valency

published · living versions

Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)

with Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai +2

1 version

W_bg4e778xv1 · current

Preprints & journals

35 papers in the corpus · 2001–2026

Consumer Understanding of Skin Concerns With an AI-Powered Informational Tool.

Sayres, Rory, Jain, Ayush, Venkatraman, Maya et al.

2 citations

419844492026JAMA dermatology. 2026;162(6):591-598

Evaluating the Utility of Personal Health Records in Personalized Health AI

Rory Sayres, Kejia Chen, Ayush Jain et al.

0 citations

2605.18937v22026arXiv

Impact of using artificial intelligence as a second reader in breast screening including arbitration.

Warren, Lucy M, Venton, Jenny, Young, Kenneth C et al.

5 citations

418078162026Nature cancer. 2026;7(3):507-521

Diagnostic accuracy, fairness and clinical implementation of AI for breast cancer screening: results of multicenter retrospective and prospective technical feasibility studies.

Kelly, Christopher J, Wilson, Marc, Warren, Lucy M et al.

16 citations

418078182026Nature cancer. 2026;7(3):494-506

Towards Better Health Conversations: The Benefits of Context-seeking

Rory Sayres, Yuexing Hao, Abbi Ward et al.

2 citations

2510.18880v12025arXiv

Closing the AI generalisation gap by adjusting for dermatology condition distribution differences across clinical settings.

Rikhye, Rajeev V, Loh, Aaron, Hong, Grace Eunhae et al.

5 citations

404606932025EBioMedicine. 2025;116:105766

Toward expert-level medical question answering with large language models.

Singhal, Karan, Tu, Tao, Gottweis, Juraj et al.

973 citations

397799262025Nature medicine. 2025;31(3):943-950

Searching for Dermatology Information Online using Images vs Text: a Randomized Study

Krogue, J. D., Sayres, R., Hartford, J. et al.

3 citations

10.1101/2024.10.25.24316155v12024medRxiv

A toolbox for surfacing health equity harms and biases in large language models.

Pfohl, Stephen R, Cole-Lewis, Heather, Sayres, Rory et al.

111 citations

393135952024Nature medicine. 2024;30(12):3590-3600

A Multiparty Collaboration to Engage Diverse Populations in Community-Centered Artificial Intelligence Research.

Devon-Sand, Anna, Sayres, Rory, Liu, Yun et al.

2 citations

402061292025Mayo Clinic proceedings. Digital health. 2024;2(3):463-469

Closing the AI generalization gap by adjusting for dermatology condition distribution differences across clinical settings

Rajeev V. Rikhye, Aaron Loh, Grace Eunhae Hong et al.

0 citations

2402.15566v12024arXiv

Differences Between Patient and Clinician-Taken Images: Implications for Virtual Care of Skin Conditions.

Rikhye, Rajeev V, Hong, Grace Eunhae, Singh, Preeti et al.

5 citations

402066822025Mayo Clinic proceedings. Digital health. 2024;2(1):107-118

Validation of a deep learning system for the detection of diabetic retinopathy in Indigenous Australians.

Chia, Mark A, Hersch, Fred, Sayres, Rory et al.

21 citations

367466152024The British journal of ophthalmology. 2024;108(2):268-273

Towards Expert-Level Medical Question Answering with Large Language Models

Karan Singhal, Tao Tu, Juraj Gottweis et al.

338 citations

2305.09617v12023arXiv

Real-time diabetic retinopathy screening by deep learning in a multisite national screening programme: a prospective interventional cohort study.

Ruamviboonsuk, Paisan, Tiwari, Richa, Sayres, Rory et al.

247 citations

352729722022The Lancet. Digital health. 2022;4(4):e235-e244

Development and Assessment of an Artificial Intelligence-Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices.

Jain, Ayush, Way, David, Gupta, Vishakha et al.

164 citations

339090552021JAMA network open. 2021;4(4):e217249

Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders.

Limwattanayingyong, Jirawut, Nganthavee, Variya, Seresirikachorn, Kasem et al.

17 citations

333816002021Journal of diabetes research. 2020;2020:8839376

Underspecification Presents Challenges for Credibility in Modern Machine Learning

Alexander D'Amour, Katherine Heller, Dan Moldovan et al.

398 citations

2011.03395v22020arXiv

Evaluation of the Use of Combined Artificial Intelligence and Pathologist Assessment to Review and Grade Prostate Biopsies.

Steiner, David F, Nagpal, Kunal, Sayres, Rory et al.

124 citations

331801292021JAMA network open. 2020;3(11):e2023267

Improving Medical Annotation Quality to Decrease Labeling Burden Using Stratified Noisy Cross-Validation

Joy Hsu, Sonia Phene, Akinori Mitani et al.

3 citations

2009.10858v12020ACM Conference on Health, Inference, and Learning, April 02-04, 2020, Toronto, Canada

Remote Tool-Based Adjudication for Grading Diabetic Retinopathy.

Schaekermann, Mike, Hammel, Naama, Terry, Michael et al.

19 citations

318671412022Translational vision science & technology. 2019;8(6):40

Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

Phene, Sonia, Dunn, R Carter, Hammel, Naama et al.

186 citations

315618792020Ophthalmology. 2019;126(12):1627-1639

Erratum: Author Correction: Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program.

Ruamviboonsuk, Paisan, Krause, Jonathan, Chotcomwongse, Peranut et al.

25 citations

313419552020NPJ digital medicine. 2019;2:68

Deep learning versus human graders for classifying diabetic retinopathy severity in a nationwide screening program.

Raumviboonsuk, Paisan, Krause, Jonathan, Chotcomwongse, Peranut et al.

232 citations

313043722020NPJ digital medicine. 2019;2:25

Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy.

Sayres, Rory, Taly, Ankur, Rahimy, Ehsan et al.

417 citations

305539002020Ophthalmology. 2019;126(4):552-564

Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program

Paisan Raumviboonsuk, Jonathan Krause, Peranut Chotcomwongse et al.

10 citations

1810.08290v12018arXiv

Direct Uncertainty Prediction for Medical Second Opinions

Maithra Raghu, Katy Blumer, Rory Sayres et al.

91 citations

1807.01771v42018arXiv

Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)

Been Kim, Martin Wattenberg, Justin Gilmer et al.

1,239 citations

1711.11279v52017ICML 2018

Mapping hV4 and ventral occipital cortex: the venous eclipse.

Winawer, Jonathan, Horiguchi, Hiroshi, Sayres, Rory A et al.

270 citations

206161432010Journal of vision. 2010;10(5):1

fMRI-adaptation and category selectivity in human ventral temporal cortex: regional differences across time scales.

Weiner, Kevin S, Sayres, Rory, Vinberg, Joakim et al.

138 citations

203752512010Journal of neurophysiology. 2010;103(6):3349-65

Relating retinotopic and object-selective responses in human lateral occipital cortex.

Sayres, Rory, Grill-Spector, Kalanit

167 citations

184631862008Journal of neurophysiology. 2008;100(1):249-67

High-resolution imaging reveals highly selective nonface clusters in the fusiform face area.

Grill-Spector, Kalanit, Sayres, Rory, Ress, David

213 citations

168920572006Nature neuroscience. 2006;9(9):1177-85

Object-selective cortex exhibits performance-independent repetition suppression.

Sayres, Rory, Grill-Spector, Kalanit

136 citations

162367872006Journal of neurophysiology. 2006;95(2):995-1007

Effect of sodium valproate on neuromagnetic responses to chromatic flicker: implication for photosensitivity.

Watanabe, K, Sayres, R, Shimojo, S et al.

0 citations

160126682006Neurology & clinical neurophysiology : NCN. 2004;2004:61

Pupillary response to chromatic flicker.

Drew, P, Sayres, R, Watanabe, K et al.

34 citations

112062882001Experimental brain research. 2001;136(2):256-62

Career total: 68 works. 35 are in this corpus.

Profile built from the corpus for this byline.

68

works

5,919

citations

23

h-index

Corpus papers per year

Corpus papers per year, 2001 to 2026. Busiest year 2024, 6 papers.
Year	Papers
2001	1
2002	0
2003	0
2004	1
2005	1
2006	1
2007	0
2008	1
2009	0
2010	2
2011	0
2012	0
2013	0
2014	0
2015	0
2016	0
2017	1
2018	4
2019	3
2020	4
2021	1
2022	1
2023	1
2024	6
2025	3
2026	4

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