Nicholas Heller

824 citations
24 papers · 82 · h-index 6

Impact in

Papers in

Nicholas Heller

19 papers receiving 80 citations

Peers

Nicholas Heller
Comparison fields: 5 of 33
  • Health Informatics 3
  • Computer Vision and Pattern Recognition 23
  • Radiology, Nuclear Medicine and Imaging 21
  • Neurology 6
  • Artificial Intelligence 24
Replace Khanh Lam with:
Khanh Lam Vietnam
M Aparicio Italy
Shishuai Hu China
Yiwen Zhang China
Paul F. Jaeger Germany
Hamza Kebiri Switzerland
Matthias Perkonigg Austria
Valentin Oreiller Switzerland
Jiang Tian China
Dennis Eschweiler Germany
Nicholas Heller relative to Khanh Lam Vietnam Khanh Lam's profile →
Citations per field
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Citations per year

Countries citing papers authored by Nicholas Heller

Since Specialization
Citations

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

Fields of papers citing papers by Nicholas Heller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Nicholas Heller, 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 Nicholas Heller Line = papers co-authored together Nicholas Heller 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 201915
2 202011
3
Computer Aided Diagnosis of Skin Lesions from Morphological Features
20188
4 20227
5 20256
6 20215
7 20205
8 20234
9 20204
10
Possible homology of ectodermal dysplasia and tabby, and possible role of egf. Abstr.
19823
11 20232
12 20232
13 20202
14 20202
15 20252
16 20201
17 20241
18 20251
19 20251
20 20250

About Nicholas Heller

Nicholas Heller is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Biomedical Engineering, Computer Vision and Pattern Recognition and Oncology, having authored 24 papers that have together received 82 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Renal cell carcinoma treatment (8 papers), Advanced X-ray and CT Imaging (4 papers), MRI in cancer diagnosis (3 papers), Surgical Simulation and Training (2 papers), Renal and Vascular Pathologies (2 papers), Cutaneous Melanoma Detection and Management (2 papers) and Artificial Intelligence in Healthcare (2 papers). The work is most often cited by research in Health Informatics (3 citations), Computer Vision and Pattern Recognition (23 citations), Radiology, Nuclear Medicine and Imaging (21 citations), Neurology (6 citations) and Artificial Intelligence (24 citations). Nicholas Heller has collaborated with scholars based in United States, Germany and Thailand. Frequent co-authors include Nikolaos Papanikolopoulos, Christopher Weight, Resha Tejpaul, Sean McSweeney, Matthew Peterson, Diana Mateus, Erick M. Remer, Paul Blake, Veronika Cheplygina and Stan R. Blecher. Their work appears in journals such as Journal of Clinical Oncology, The Journal of Urology, PLoS ONE, British Journal of Urology and Cancer Research.

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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