Peter Speltz
Impact in
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- Electronic Health Records Systems
- Artificial Intelligence in Healthcare
- Health Informatics top 5%
Papers in
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- Biomedical Text Mining and Ontologies 8
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- Scientific Computing and Data Management 4
- Co-authors
- Joshua C. Denny (11 shared papers)Luke V. Rasmussen (7 shared papers)Jyotishman Pathak (6 shared papers)Jennifer A. Pacheco (7 shared papers)Melissa Basford (2 shared papers)Dan M. Roden (3 shared papers)Jonathan L. Haines (1 shared paper)David Carrell (1 shared paper)
- Journals
- Journal of the American Medical Informatics Association (3 papers)Pharmacogenomics (1 paper)Journal of Biomedical Informatics (1 paper)AMIA (2 papers)PubMed (3 papers)
- Partner nations
- United States
In The Last Decade
Peter Speltz
11 papers receiving 394 citations
Peers
Comparison fields: 5 of 73
- Health Information Management 100
- Health Informatics 27
- Computational Mathematics 4
- Family Practice 15
- Pharmacology 50
Countries citing papers authored by Peter Speltz
This map shows the geographic impact of Peter Speltz'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 Peter Speltz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Speltz more than expected).
Fields of papers citing papers by Peter Speltz
This network shows the impact of papers produced by Peter Speltz. 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 Peter Speltz. The network helps show where Peter Speltz may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Speltz, 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 | 2016 | 238 | |
| 2 | 2012 | 70 | |
| 3 | 2015 | 28 | |
| 4 | 2015 | 26 | |
| 5 | A Modular Architecture for Electronic Health Record-Driven Phenotyping. | 2015 | 16 |
| 6 | A Prototype for Executable and Portable Electronic Clinical Quality Measures Using the KNIME Analytics Platform. | 2015 | 7 |
| 7 | 2020 | 6 | |
| 8 | Harmonization of Quality Data Model with HL7 FHIR to Support EHR-driven Phenotype Authoring and Execution: A Pilot Study. | 2015 | 2 |
| 9 | Comparing content coverage in medical curriculum to trainee-authored clinical notes. | 2010 | 2 |
| 10 | 2018 | 2 | |
| 11 | Evaluation of Existing Phenotype Authoring Tools for Clinical Research. | 2014 | 1 |
About Peter Speltz
Peter Speltz is a scholar working on Molecular Biology, Information Systems and Management, Artificial Intelligence, Health Information Management and General Health Professions, having authored 11 papers that have together received 398 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (8 papers), Scientific Computing and Data Management (4 papers), Electronic Health Records Systems (3 papers), Machine Learning in Healthcare (3 papers), Health Sciences Research and Education (2 papers), Pharmacogenetics and Drug Metabolism (2 papers), Clinical Reasoning and Diagnostic Skills (2 papers) and Metabolism and Genetic Disorders (1 paper). The work is most often cited by research in Health Information Management (100 citations), Health Informatics (27 citations), Computational Mathematics (4 citations), Family Practice (15 citations) and Pharmacology (50 citations). Peter Speltz has collaborated with scholars based in United States. Frequent co-authors include Joshua C. Denny, Luke V. Rasmussen, Jyotishman Pathak, Jennifer A. Pacheco, Melissa Basford, Dan M. Roden, Jonathan L. Haines, David Carrell, Stephen B. Ellis and Peggy Peissig. Their work appears in journals such as Journal of the American Medical Informatics Association, Pharmacogenomics, Journal of Biomedical Informatics, AMIA and PubMed.
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.