Pedro Leuschner
Impact in
- Health Information Management top 10%
- Electronic Health Records Systems
- Artificial Intelligence in Healthcare
Papers in
-
- Electronic Health Records Systems 5
- Artificial Intelligence in Healthcare 2
-
- Machine Learning in Healthcare 2
- Semantic Web and Ontologies 1
- Co-authors
- António Abelha (6 shared papers)José Machado (4 shared papers)Manuel Filipe Santos (3 shared papers)João Pedro Ferreira (2 shared papers)Heidi Dorward (1 shared paper)Wendy J. Introne (1 shared paper)João Sérgio Neves (1 shared paper)Filipe Froes (1 shared paper)
- Journals
- Scientific Reports (1 paper)European Respiratory Journal (1 paper)Pulmonology (1 paper)American Journal of Medical Genetics Part A (1 paper)Health and Technology (1 paper)
- Partner nations
- PortugalUnited StatesAustralia
In The Last Decade
Pedro Leuschner
10 papers receiving 59 citations
Peers
Comparison fields: 5 of 39
- Health Information Management 27
- Health Informatics 1
- Management Information Systems 6
- Medical Laboratory Technology 1
- Management Science and Operations Research 8
Countries citing papers authored by Pedro Leuschner
This map shows the geographic impact of Pedro Leuschner'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 Pedro Leuschner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pedro Leuschner more than expected).
Fields of papers citing papers by Pedro Leuschner
This network shows the impact of papers produced by Pedro Leuschner. 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 Pedro Leuschner. The network helps show where Pedro Leuschner may publish in the future.
Co-authors
The 22 scholars most cited alongside Pedro Leuschner, 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 | 2020 | 12 | |
| 2 | 2021 | 11 | |
| 3 | 2020 | 8 | |
| 4 | 2022 | 7 | |
| 5 | 2021 | 7 | |
| 6 | 2020 | 6 | |
| 7 | 2019 | 3 | |
| 8 | 2025 | 3 | |
| 9 | [Von Meyenburg complex or liver metastasis? Case report and literature review]. | 2015 | 2 |
| 10 | 2014 | 1 |
About Pedro Leuschner
Pedro Leuschner is a scholar working on Health Information Management, Artificial Intelligence, Pulmonary and Respiratory Medicine, Epidemiology and Public Health, Environmental and Occupational Health, having authored 10 papers that have together received 60 indexed citations. Recurring topics across this work include Electronic Health Records Systems (5 papers), COVID-19 diagnosis using AI (2 papers), Artificial Intelligence in Healthcare (2 papers), Telemedicine and Telehealth Implementation (2 papers), Pneumonia and Respiratory Infections (2 papers), Machine Learning in Healthcare (2 papers), Business Process Modeling and Analysis (1 paper) and Semantic Web and Ontologies (1 paper). The work is most often cited by research in Health Information Management (27 citations), Health Informatics (1 citation), Management Information Systems (6 citations), Medical Laboratory Technology (1 citation) and Management Science and Operations Research (8 citations). Pedro Leuschner has collaborated with scholars based in Portugal, United States and Australia. Frequent co-authors include António Abelha, José Machado, Manuel Filipe Santos, João Pedro Ferreira, Heidi Dorward, Wendy J. Introne, João Sérgio Neves, Filipe Froes, Paula Pinto and Camilo Toro. Their work appears in journals such as Scientific Reports, European Respiratory Journal, Pulmonology, American Journal of Medical Genetics Part A and Health and Technology.
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.