Cleo‐Aron Weis
Impact in
- Health Informatics top 2%
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
- Neurology 19
- Myasthenia Gravis and Thymoma 19
- Peripheral Neuropathies and Disorders 5
- Co-authors
- Alexander MarxJakob Nikolas KatherTimo GaiserPhilipp StröbelLothar R. SchadFrank G. ZöllnerEsther HerpelSusanne Melchers
- Journals
- Scientific Reports (6 papers)Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin (3 papers)Diagnostic Pathology (3 papers)PLoS ONE (3 papers)Journal of Thoracic Oncology (2 papers)
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Cleo‐Aron Weis
66 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Health Informatics 50
- Radiology, Nuclear Medicine and Imaging 713
- Artificial Intelligence 844
- Oncology 703
- Neurology 390
Countries citing papers authored by Cleo‐Aron Weis
This map shows the geographic impact of Cleo‐Aron Weis'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 Cleo‐Aron Weis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cleo‐Aron Weis more than expected).
Fields of papers citing papers by Cleo‐Aron Weis
This network shows the impact of papers produced by Cleo‐Aron Weis. 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 Cleo‐Aron Weis. The network helps show where Cleo‐Aron Weis may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Cleo‐Aron Weis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 4 | |
| 6 | 2022 | 24 | |
| 7 | 2021 | 5 | |
| 8 | 2021 | 2 | |
| 9 | 2020 | 6 | |
| 10 | 2019 | 15 | |
| 11 | Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study Hit paper breakdown → | 2019 | 611 |
| 12 | 2019 | 17 | |
| 13 | 2019 | 40 | |
| 14 | 2018 | 9 | |
| 15 | 2018 | 8 | |
| 16 | 2018 | 4 | |
| 17 | 2017 | 79 | |
| 18 | 2016 | 15 | |
| 19 | 2015 | 63 | |
| 20 | 2014 | 135 |
About Cleo‐Aron Weis
Cleo‐Aron Weis is a scholar working on Neurology, Health Informatics, Oncology, Biophysics and Endocrinology, Diabetes and Metabolism, having authored 71 papers that have together received 2.3k indexed citations. Recurring topics across this work include Myasthenia Gravis and Thymoma (19 papers), AI in cancer detection (13 papers), Bladder and Urothelial Cancer Treatments (11 papers), Urinary and Genital Oncology Studies (9 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Pituitary Gland Disorders and Treatments (7 papers), Peripheral Neuropathies and Disorders (5 papers) and Colorectal Cancer Screening and Detection (4 papers). The work is most often cited by research in Health Informatics (50 citations), Radiology, Nuclear Medicine and Imaging (713 citations), Artificial Intelligence (844 citations), Oncology (703 citations) and Neurology (390 citations). Cleo‐Aron Weis has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Alexander Marx, Jakob Nikolas Kather, Timo Gaiser, Philipp Ströbel, Lothar R. Schad, Frank G. Zöllner, Esther Herpel, Susanne Melchers, Niels Halama and Dirk Jäger. Their work appears in journals such as Scientific Reports, Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin, Diagnostic Pathology, PLoS ONE and Journal of Thoracic Oncology.
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.