Gregory Holste

606 total citations · 1 hit paper
21 papers, 257 citations indexed

About

Gregory Holste is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Artificial Intelligence. According to data from OpenAlex, Gregory Holste has authored 21 papers receiving a total of 257 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Cardiology and Cardiovascular Medicine and 6 papers in Artificial Intelligence. Recurrent topics in Gregory Holste's work include COVID-19 diagnosis using AI (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and AI in cancer detection (5 papers). Gregory Holste is often cited by papers focused on COVID-19 diagnosis using AI (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and AI in cancer detection (5 papers). Gregory Holste collaborates with scholars based in United States, United Kingdom and Hungary. Gregory Holste's co-authors include Zhangyang Wang, Rohan Khera, Evangelos K. Oikonomou, Adam Alessio, Yifan Peng, Habib Rahbar, Christoph I. Lee, Savannah C. Partridge, Robert L. McNamara and Harlan M. Krumholz and has published in prestigious journals such as JAMA, Circulation and Nature Communications.

In The Last Decade

Gregory Holste

19 papers receiving 251 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.

Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study

2025 15 citations Evangelos K. Oikonomou, Akhil Vaid et al. The Lancet Digital Health profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gregory Holste United States	10	139	82	78	60	34	21	257
Michail Mamalakis United Kingdom	9	157 1.1×	33 0.4×	70 0.9×	37 0.6×	32 0.9×	19	245
Guilherme Silva Brazil	6	166 1.2×	132 1.6×	111 1.4×	35 0.6×	33 1.0×	18	333
Carlos Martín-Isla Spain	9	219 1.6×	106 1.3×	64 0.8×	45 0.8×	27 0.8×	14	371
Geunyoung Lee Singapore	13	361 2.6×	40 0.5×	48 0.6×	38 0.6×	15 0.4×	20	464
P. Ignacio Dorado-Díaz Spain	7	66 0.5×	77 0.9×	30 0.4×	52 0.9×	11 0.3×	12	179
Jesús Sampedro-Gómez Spain	7	66 0.5×	77 0.9×	30 0.4×	52 0.9×	11 0.3×	12	179
Hitoshi Mori Japan	9	98 0.7×	199 2.4×	135 1.7×	42 0.7×	31 0.9×	65	449
Esther Puyol‐Antón United Kingdom	12	262 1.9×	247 3.0×	55 0.7×	54 0.9×	20 0.6×	40	481
Grant Duffy United States	8	156 1.1×	189 2.3×	45 0.6×	73 1.2×	32 0.9×	14	331
Wei-Yin Ko United States	4	44 0.3×	168 2.0×	31 0.4×	33 0.6×	42 1.2×	7	218

Countries citing papers authored by Gregory Holste

Since Specialization

Citations

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

Fields of papers citing papers by Gregory Holste

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregory Holste. 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 Gregory Holste. The network helps show where Gregory Holste may publish in the future.

Co-authorship network of co-authors of Gregory Holste

This figure shows the co-authorship network connecting the top 25 collaborators of Gregory Holste. A scholar is included among the top collaborators of Gregory Holste 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 Gregory Holste. Gregory Holste 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

Holste, Gregory, et al.. (2025). Artificial Intelligence-Enabled Echocardiography as a Surrogate for Multimodality Aortic Stenosis Imaging: Post Hoc Analysis of a Clinical Trial. Circulation Cardiovascular Imaging. 19(2). e018353–e018353.

Oikonomou, Evangelos K., Akhil Vaid, Gregory Holste, et al.. (2025). Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study. The Lancet Digital Health. 7(2). e113–e123. 15 indexed citations breakdown →

Holste, Gregory, Evangelos K. Oikonomou, & Rohan Khera. (2025). AI-Enabled Echocardiography Interpretation With Multitask Deep Learning—Reply. JAMA. 334(21). 1954–1954.

Holste, Gregory, Evangelos Oikonomou, Márton Tokodi, et al.. (2025). Complete AI-Enabled Echocardiography Interpretation With Multitask Deep Learning. JAMA. 334(4). 306–306. 11 indexed citations

Sangha, Veer, Akshay Khunte, Gregory Holste, et al.. (2024). Biometric contrastive learning for data-efficient deep learning from electrocardiographic images. Journal of the American Medical Informatics Association. 31(4). 855–865. 11 indexed citations

Holste, Gregory, Jeffrey P. Otjen, Francisco A. Perez, et al.. (2024). High sensitivity methods for automated rib fracture detection in pediatric radiographs. Scientific Reports. 14(1). 8372–8372. 1 indexed citations

Holste, Gregory, Evangelos K. Oikonomou, Bobak J. Mortazavi, Zhangyang Wang, & Rohan Khera. (2024). Efficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning. SHILAP Revista de lepidopterología. 4(1). 133–133. 10 indexed citations

Lin, Mingquan, Zhaoyi Sun, Gregory Holste, et al.. (2024). Improving Fairness of Automated Chest Radiograph Diagnosis by Contrastive Learning. Radiology Artificial Intelligence. 6(5). e230342–e230342. 4 indexed citations

Oikonomou, Evangelos K., Gregory Holste, Girish N. Nadkarni, Zhangyang Wang, & Rohan Khera. (2024). CROSS-MODAL VALIDATION OF AN ARTIFICIAL INTELLIGENCE VIDEO-BASED APPROACH FOR THE AUTOMATED RISK STRATIFICATION OF AORTIC STENOSIS. Journal of the American College of Cardiology. 83(13). 1418–1418. 1 indexed citations

10.

Oikonomou, Evangelos K., Gregory Holste, Neal Yuan, et al.. (2024). A Multimodal Video-Based AI Biomarker for Aortic Stenosis Development and Progression. JAMA Cardiology. 9(6). 534–534. 32 indexed citations

11.

Holste, Gregory, Evangelos K. Oikonomou, Bobak J. Mortazavi, et al.. (2023). Severe aortic stenosis detection by deep learning applied to echocardiography. European Heart Journal. 44(43). 4592–4604. 57 indexed citations

12.

Lin, Mingquan, Yifan Yang, Gregory Holste, et al.. (2023). Improving model fairness in image-based computer-aided diagnosis. Nature Communications. 14(1). 6261–6261. 15 indexed citations

13.

Holste, Gregory, Ziyu Jiang, Ajay Jaiswal, et al.. (2023). How Does Pruning Impact Long-Tailed Multi-label Medical Image Classifiers?. Lecture notes in computer science. 14224. 663–673. 1 indexed citations

14.

Holste, Gregory, et al.. (2023). Improved Multimodal Fusion for Small Datasets with Auxiliary Supervision. 1–5. 2 indexed citations

15.

Khunte, Akshay, Veer Sangha, Gregory Holste, et al.. (2023). Abstract 18776: ECG-GPT: Automated Complete Diagnosis Generation From ECG Images Using Novel Vision-Text Transformer Model. Circulation. 148(Suppl_1). 2 indexed citations

16.

Holste, Gregory, Song Wang, Ziyu Jiang, et al.. (2022). Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study. Lecture notes in computer science. 13567. 22–32. 25 indexed citations

17.

Holste, Gregory, et al.. (2022). Avalanche decision schemes to improve pediatric rib fracture detection. 107–107. 5 indexed citations

18.

Holste, Gregory, et al.. (2022). Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rays. IEEE Transactions on Medical Imaging. 42(3). 750–761. 17 indexed citations

19.

Holste, Gregory, et al.. (2020). Multi-class semantic segmentation of pediatric chest radiographs. 49–49. 5 indexed citations

20.

Holste, Gregory, et al.. (2020). Deep learning methods for segmentation of lines in pediatric chest radiographs. 87–87. 2 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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