David P. vanMaanen
- Cardiology and Cardiovascular Medicine
- Radiology, Nuclear Medicine and Imaging
- Cognitive Neuroscience
- Cellular and Molecular Neuroscience
- Molecular Biology
- Co-authors
- Peter J. SiekmeierH. Lester KirchnerAlvaro UlloaChristopher W. GoodJoseph B. LeaderJonathan D SueverChristopher M. HaggertySushravya Raghunath
- Topics
- Neural dynamics and brain function (2 papers)Machine Learning in Healthcare (2 papers)Neuroscience and Neuropharmacology Research (2 papers)
- Cited by
- Health InformaticsCardiology and Cardiovascular MedicineRadiology, Nuclear Medicine and Imaging
- Partner nations
- United States
In The Last Decade
David P. vanMaanen
6 papers receiving 74 citations
Peers
Comparison fields: 5 of 38
- Cardiology and Cardiovascular Medicine 30
- Radiology, Nuclear Medicine and Imaging 29
- Cognitive Neuroscience 18
- Cellular and Molecular Neuroscience 13
- Molecular Biology 10
Countries citing papers authored by David P. vanMaanen
This map shows the geographic impact of David P. vanMaanen'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 David P. vanMaanen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David P. vanMaanen more than expected).
Fields of papers citing papers by David P. vanMaanen
This network shows the impact of papers produced by David P. vanMaanen. 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 David P. vanMaanen. The network helps show where David P. vanMaanen may publish in the future.
Co-authorship network of co-authors of David P. vanMaanen
This figure shows the co-authorship network connecting the top 25 collaborators of David P. vanMaanen. A scholar is included among the top collaborators of David P. vanMaanen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David P. vanMaanen. David P. vanMaanen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 45 | |
| 5 | Abstract 14425: Deep Neural Networks Can Predict 1-Year Mortality Directly From ECG Signal, Even When Clinically Interpreted as Normal | 2 |
| 6 | A deep neural network predicts survival after heart imaging better than cardiologists. | 2 |
| 7 | 6 | |
| 8 | 16 |
About David P. vanMaanen
David P. vanMaanen is a scholar working on Health Information Management, Cellular and Molecular Neuroscience and Cognitive Neuroscience, having authored 8 papers that have together received 74 indexed citations. Recurring topics across this work include Neural dynamics and brain function (2 papers), Machine Learning in Healthcare (2 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Health Informatics (6 citations), Cardiology and Cardiovascular Medicine (30 citations) and Radiology, Nuclear Medicine and Imaging (29 citations). David P. vanMaanen has collaborated with scholars based in United States. Frequent co-authors include Peter J. Siekmeier, H. Lester Kirchner, Alvaro Ulloa, Christopher W. Good, Joseph B. Leader, Jonathan D Suever, Christopher M. Haggerty, Sushravya Raghunath, Linyuan Jing and Dustin N. Hartzel. Their work appears in journals such as Circulation, PLoS ONE and Neuropsychopharmacology.
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.