David Coz

642 total citations · 1 hit paper
5 papers, 362 citations indexed

About

David Coz is a scholar working on Artificial Intelligence, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, David Coz has authored 5 papers receiving a total of 362 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Oncology and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in David Coz's work include Retinal Imaging and Analysis (2 papers), Cutaneous Melanoma Detection and Management (2 papers) and Imbalanced Data Classification Techniques (1 paper). David Coz is often cited by papers focused on Retinal Imaging and Analysis (2 papers), Cutaneous Melanoma Detection and Management (2 papers) and Imbalanced Data Classification Techniques (1 paper). David Coz collaborates with scholars based in United States. David Coz's co-authors include Dale R. Webster, Rory Sayres, Greg S. Corrado, Lily Peng, Zahra Rastegar, Derek Wu, Shawn Xu, Jonathan Krause, Scott Barb and Anthony Joseph and has published in prestigious journals such as Ophthalmology, Investigative Ophthalmology & Visual Science and JAMA Network Open.

In The Last Decade

David Coz

5 papers receiving 352 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.

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

2018 250 citations Rory Sayres, Ankur Taly et al. Ophthalmology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Coz United States	4	189	127	106	82	50	5	362
Agostina J. Larrazabal Argentina	2	137 0.7×	131 1.0×	24 0.2×	160 2.0×	33 0.7×	5	380
Saad Khan United Kingdom	5	157 0.8×	37 0.3×	111 1.0×	50 0.6×	22 0.4×	7	263
Daniel T. Hogarty Australia	7	187 1.0×	50 0.4×	155 1.5×	34 0.4×	21 0.4×	10	364
Abigail E. Huang United States	8	225 1.2×	58 0.5×	172 1.6×	39 0.5×	59 1.2×	14	377
Zahra Rastegar United States	4	214 1.1×	84 0.7×	124 1.2×	47 0.6×	37 0.7×	8	331
Ying-Chun Jheng Taiwan	11	192 1.0×	41 0.3×	125 1.2×	31 0.4×	37 0.7×	23	345
Shawn Xu United States	3	175 0.9×	82 0.6×	106 1.0×	48 0.6×	37 0.7×	4	280
Jocelyn Hui Lin Goh Singapore	6	198 1.0×	94 0.7×	77 0.7×	203 2.5×	27 0.5×	12	366
Yeganeh Madadi United States	9	141 0.7×	73 0.6×	63 0.6×	120 1.5×	31 0.6×	17	249
Peter A. Karth United States	12	469 2.5×	68 0.5×	473 4.5×	42 0.5×	72 1.4×	23	716

Countries citing papers authored by David Coz

Since Specialization

Citations

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

Fields of papers citing papers by David Coz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Coz

This figure shows the co-authorship network connecting the top 25 collaborators of David Coz. A scholar is included among the top collaborators of David Coz 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 Coz. David Coz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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5 of 5 papers shown

1.

Jain, Ayush, Yi Gao, Rory Sayres, et al.. (2021). Development and Assessment of an Artificial Intelligence–Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices. JAMA Network Open. 4(4). e217249–e217249. 90 indexed citations

2.

Lee, Kang, David Coz, Christof Angermueller, et al.. (2020). Agreement Between Saliency Maps and Human-Labeled Regions of Interest: Applications to Skin Disease Classification. 3172–3181. 8 indexed citations

3.

Ghorbani, Amirata, Vivek Natarajan, David Coz, & Yuan Liu. (2019). DermGAN: Synthetic Generation of Clinical Skin Images with Pathology. 155–170. 12 indexed citations

4.

Sayres, Rory, Ankur Taly, Ehsan Rahimy, et al.. (2018). Assisted reads for diabetic retinopathy using a deep learning algorithm and integrated gradient explanation. Investigative Ophthalmology & Visual Science. 59(9). 1227–1227. 2 indexed citations

5.

Sayres, Rory, Ankur Taly, Ehsan Rahimy, et al.. (2018). Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy. Ophthalmology. 126(4). 552–564. 250 indexed citations breakdown →

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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