Peter Speltz

799 citations
12 papers · 430 · h-index 7

Impact in

Papers in

Peter Speltz

12 papers receiving 426 citations

Peers

Peter Speltz
Comparison fields: 5 of 67
  • Health Information Management 77
  • Health Informatics 23
  • Pharmacology 47
  • Computational Mathematics 3
  • Family Practice 6
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Citations per year

Countries citing papers authored by Peter Speltz

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Peter Speltz Line = papers co-authored together Peter Speltz links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2016252
2 201273
3 201530
4 201530
5
A Modular Architecture for Electronic Health Record-Driven Phenotyping.
201515
6 20159
7
A Prototype for Executable and Portable Electronic Clinical Quality Measures Using the KNIME Analytics Platform.
20158
8 20206
9
Harmonization of Quality Data Model with HL7 FHIR to Support EHR-driven Phenotype Authoring and Execution: A Pilot Study.
20152
10 20182
11
Comparing content coverage in medical curriculum to trainee-authored clinical notes.
20102
12
Evaluation of Existing Phenotype Authoring Tools for Clinical Research.
20141

About Peter Speltz

Peter Speltz is a scholar working on Molecular Biology, Information Systems and Management, Health Information Management, Artificial Intelligence and Pharmacology, having authored 12 papers that have together received 430 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (7 papers), Scientific Computing and Data Management (4 papers), Electronic Health Records Systems (3 papers), Pharmacogenetics and Drug Metabolism (2 papers), Machine Learning in Healthcare (2 papers), Clinical Reasoning and Diagnostic Skills (1 paper), Statistical Methods in Clinical Trials (1 paper) and Pharmacovigilance and Adverse Drug Reactions (1 paper). The work is most often cited by research in Health Information Management (77 citations), Health Informatics (23 citations), Pharmacology (47 citations), Computational Mathematics (3 citations) and Family Practice (6 citations). Peter Speltz has collaborated with scholars based in United States. Frequent co-authors include Joshua C. Denny, Jyotishman Pathak, Luke V. Rasmussen, Jennifer A. Pacheco, Dan M. Roden, Melissa Basford, Stephen B. Ellis, Peggy Peissig, Gerard Tromp and Paul A. Harris. Their work appears in journals such as Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, Pharmacogenomics, Studies in health technology and informatics 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.

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