Max Horn
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Family Practice top 10%
- Clinical Reasoning and Diagnostic Skills
Papers in
-
- Sepsis Diagnosis and Treatment 5
- Herpesvirus Infections and Treatments 2
-
- Machine Learning in Healthcare 5
- Co-authors
- Bastian Rieck (9 shared papers)Karsten Borgwardt (10 shared papers)Michael Moor (8 shared papers)Catherine R. Jutzeler (2 shared papers)Christian Bock (3 shared papers)Thomas Gumbsch (2 shared papers)Marc Zimmermann (1 shared paper)Gunnar Rätsch (1 shared paper)
- Journals
- Nature Medicine (2 papers)Nature Communications (1 paper)EClinicalMedicine (1 paper)Alzheimer s & Dementia (1 paper)Molecular BioSystems (1 paper)
- Partner nations
- SwitzerlandUnited StatesGermany
In The Last Decade
Max Horn
15 papers receiving 533 citations
Max Horn's Hit Papers
Peers
Comparison fields: 5 of 101
- Health Informatics 47
- Family Practice 22
- Health Information Management 34
- Epidemiology 185
- Artificial Intelligence 154
Countries citing papers authored by Max Horn
This map shows the geographic impact of Max Horn'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 Max Horn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Max Horn more than expected).
Fields of papers citing papers by Max Horn
This network shows the impact of papers produced by Max Horn. 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 Max Horn. The network helps show where Max Horn may publish in the future.
Co-authors
The 25 scholars most cited alongside Max Horn, 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 | Early prediction of circulatory failure in the intensive care unit using machine learning Hit paper breakdown → | 2020 | 250 |
| 2 | 2021 | 114 | |
| 3 | 2023 | 40 | |
| 4 | 2017 | 39 | |
| 5 | 2020 | 23 | |
| 6 | 2015 | 20 | |
| 7 | 2020 | 13 | |
| 8 | Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis. | 2019 | 13 |
| 9 | Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology | 2019 | 10 |
| 10 | 2025 | 7 | |
| 11 | 2023 | 7 | |
| 12 | Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping | 2019 | 3 |
| 13 | 2023 | 3 | |
| 14 | 2024 | 2 | |
| 15 | 2020 | 2 | |
| 16 | 2025 | 0 | |
| 17 | 2024 | 0 |
About Max Horn
Max Horn is a scholar working on Epidemiology, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Molecular Biology, having authored 17 papers that have together received 546 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (5 papers), Sepsis Diagnosis and Treatment (5 papers), Herpesvirus Infections and Treatments (2 papers), Clinical Reasoning and Diagnostic Skills (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Time Series Analysis and Forecasting (2 papers), Bacterial Genetics and Biotechnology (2 papers) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Health Informatics (47 citations), Family Practice (22 citations), Health Information Management (34 citations), Epidemiology (185 citations) and Artificial Intelligence (154 citations). Max Horn has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include Bastian Rieck, Karsten Borgwardt, Michael Moor, Catherine R. Jutzeler, Christian Bock, Thomas Gumbsch, Marc Zimmermann, Gunnar Rätsch, Cristóbal Esteban and Xinrui Lyu. Their work appears in journals such as Nature Medicine, Nature Communications, EClinicalMedicine, Alzheimer s & Dementia and Molecular BioSystems.
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.