Michael Moor
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Ultrasound in Clinical Applications
Papers in
- Epidemiology 11
- Sepsis Diagnosis and Treatment 7
- Infective Endocarditis Diagnosis and Management 2
- Congenital Heart Disease Studies 2
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- Machine Learning in Healthcare 6
- Co-authors
- Bastian Rieck (12 shared papers)Karsten Borgwardt (13 shared papers)Max Horn (8 shared papers)Catherine R. Jutzeler (3 shared papers)Christian Bock (6 shared papers)Thomas Gumbsch (4 shared papers)Gunnar Rätsch (1 shared paper)Martin Faltys (1 shared paper)
- Journals
- Bioinformatics (3 papers)International Journal of Cardiology (2 papers)EClinicalMedicine (1 paper)Nature Medicine (1 paper)JAMA Network Open (1 paper)
- Partner nations
- SwitzerlandUnited StatesSouth Africa
In The Last Decade
Michael Moor
24 papers receiving 810 citations
Michael Moor's Hit Papers
Peers
Comparison fields: 5 of 121
- Health Informatics 77
- Critical Care and Intensive Care Medicine 64
- Family Practice 22
- Health Information Management 43
- Radiology, Nuclear Medicine and Imaging 150
Countries citing papers authored by Michael Moor
This map shows the geographic impact of Michael Moor'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 Michael Moor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Moor more than expected).
Fields of papers citing papers by Michael Moor
This network shows the impact of papers produced by Michael Moor. 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 Michael Moor. The network helps show where Michael Moor may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael Moor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Early prediction of circulatory failure in the intensive care unit using machine learning Hit paper breakdown → | 2020 | 260 |
| 2 | 2021 | 120 | |
| 3 | 2021 | 116 | |
| 4 | 2021 | 111 | |
| 5 | 2023 | 41 | |
| 6 | Multimodal generative AI for medical image interpretation Hit paper breakdown → | 2025 | 31 |
| 7 | 2020 | 19 | |
| 8 | 2018 | 17 | |
| 9 | Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis. | 2019 | 14 |
| 10 | 2020 | 13 | |
| 11 | 2024 | 13 | |
| 12 | Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology | 2019 | 11 |
| 13 | 1986 | 10 | |
| 14 | 2022 | 8 | |
| 15 | 2023 | 8 | |
| 16 | 2025 | 7 | |
| 17 | 2023 | 6 | |
| 18 | 1989 | 6 | |
| 19 | 1988 | 5 | |
| 20 | 1986 | 3 |
About Michael Moor
Michael Moor is a scholar working on Epidemiology, Artificial Intelligence, Surgery, Signal Processing and Pulmonary and Respiratory Medicine, having authored 24 papers that have together received 829 indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (7 papers), Machine Learning in Healthcare (6 papers), Time Series Analysis and Forecasting (4 papers), Topological and Geometric Data Analysis (2 papers), Cell Image Analysis Techniques (2 papers), Infective Endocarditis Diagnosis and Management (2 papers), Clinical Reasoning and Diagnostic Skills (2 papers) and Congenital Heart Disease Studies (2 papers). The work is most often cited by research in Health Informatics (77 citations), Critical Care and Intensive Care Medicine (64 citations), Family Practice (22 citations), Health Information Management (43 citations) and Radiology, Nuclear Medicine and Imaging (150 citations). Michael Moor has collaborated with scholars based in Switzerland, United States and South Africa. Frequent co-authors include Bastian Rieck, Karsten Borgwardt, Max Horn, Catherine R. Jutzeler, Christian Bock, Thomas Gumbsch, Gunnar Rätsch, Martin Faltys, Dean A. Bodenham and Stephanie L. Hyland. Their work appears in journals such as Bioinformatics, International Journal of Cardiology, EClinicalMedicine, Nature Medicine and JAMA Network Open.
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.