David Dov

22 papers receiving 338 citations

Peers

David Dov
Comparison fields: 5 of 74
  • Health Informatics 38
  • Signal Processing 99
  • Radiology, Nuclear Medicine and Imaging 158
  • Ophthalmology 44
  • Artificial Intelligence 152
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Aaron Loh United States
Yin Dai China
Hung N. Pham Vietnam
Chaoyu Chen China
Jahanzaib Latif China
Yanda Meng United Kingdom
Rayan Krishnan United States
Noor Ayesha China
Anam Fatima Pakistan
Nitin Singhal South Korea
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Countries citing papers authored by David Dov

Since Specialization
Citations

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

Fields of papers citing papers by David Dov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Dov, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Dov Line = papers co-authored together David Dov links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202071
2 202046
3 202044
4 201539
5 202122
6 201722
7 201619
8 201613
9 202311
10 202111
11 20149
12 20178
13 20217
14 20236
15
Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images
20196
16 20206
17
A Deep-Learning Algorithm for Thyroid Malignancy Prediction From Whole Slide Cytopathology Images.
20195
18 20175
19 20182
20
A Deep Learning-Based Mapping of Structure to Function in Glaucoma
20201

About David Dov

David Dov is a scholar working on Artificial Intelligence, Signal Processing, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 24 papers that have together received 356 indexed citations. Recurring topics across this work include Speech and Audio Processing (10 papers), AI in cancer detection (8 papers), Music and Audio Processing (8 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Advanced Adaptive Filtering Techniques (4 papers), Speech Recognition and Synthesis (3 papers), Cervical Cancer and HPV Research (3 papers) and Thyroid Cancer Diagnosis and Treatment (3 papers). The work is most often cited by research in Health Informatics (38 citations), Signal Processing (99 citations), Radiology, Nuclear Medicine and Imaging (158 citations), Ophthalmology (44 citations) and Artificial Intelligence (152 citations). David Dov has collaborated with scholars based in Israel, United States and Saudi Arabia. Frequent co-authors include Israel Cohen, Lawrence Carin, Ronen Talmon, Ricardo Henao, Jonathan Cohen, Shahar Z. Kovalsky, Geoffrey D. Rubin, Maciej A. Mazurowski, Joseph Y. Lo and Rachel Lea Draelos. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Archives of Pathology & Laboratory Medicine, IEEE Transactions on Signal Processing, The Journal of Heart and Lung Transplantation and Translational Vision Science & Technology.

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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