Stefan Coors
- Health Informatics top 10%
- Computer Science Applications top 10%
- Online Learning and Analytics 1
- Artificial Intelligence top 10%
- Machine Learning and Data Classification 4
- Metaheuristic Optimization Algorithms Research 2
- Health Information Management top 10%
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- Advanced Multi-Objective Optimization Algorithms 2
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- Radiomics and Machine Learning in Medical Imaging 1
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- Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes 1
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- Second Language Acquisition and Learning 1
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- Renal cell carcinoma treatment 1
- Co-authors
- Bernd BischlMartin BinderMichel LangJakob RichterTobias PielokJanek ThomasDifan DengMarc Becker
- Journals
- Investigative Radiology (1 paper)European Archives of Psychiatry and Clinical Neuroscience (1 paper)Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (1 paper)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
Stefan Coors
7 papers receiving 716 citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Health Informatics 12
- Computer Science Applications 36
- Artificial Intelligence 200
- Environmental Engineering 58
- Health Information Management 17
Countries citing papers authored by Stefan Coors
This map shows the geographic impact of Stefan Coors'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 Stefan Coors with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefan Coors more than expected).
Fields of papers citing papers by Stefan Coors
This network shows the impact of papers produced by Stefan Coors. 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 Stefan Coors. The network helps show where Stefan Coors may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Stefan Coors, 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 | 2024 | 1 | |
| 2 | 2023 | 36 | |
| 3 | 2023 | 13 | |
| 4 | Hyperparameter optimization: Foundations, algorithms, best practices, and open challengesbreakdown → | 2023 | 398 |
| 5 | 2021 | 49 | |
| 6 | 2019 | 235 | |
| 7 | 2018 | 7 |
About Stefan Coors
Stefan Coors is a scholar working on Applied Psychology, Computer Science Applications and Artificial Intelligence, having authored 7 papers that have together received 739 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (4 papers), Advanced Multi-Objective Optimization Algorithms (2 papers), Metaheuristic Optimization Algorithms Research (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (1 paper), Online Learning and Analytics (1 paper), Second Language Acquisition and Learning (1 paper) and Renal cell carcinoma treatment (1 paper). The work is most often cited by research in Health Informatics (12 citations), Computer Science Applications (36 citations) and Artificial Intelligence (200 citations). Stefan Coors has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Bernd Bischl, Martin Binder, Michel Lang, Jakob Richter, Tobias Pielok, Janek Thomas, Difan Deng, Marc Becker, Marius Lindauer and Theresa Ullmann. Their work appears in journals such as Investigative Radiology, European Archives of Psychiatry and Clinical Neuroscience and Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery.
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.