Janice S. Aikins
- Artificial Intelligence top 10%
- AI-based Problem Solving and Planning 5
- Semantic Web and Ontologies 4
- Multi-Agent Systems and Negotiation 2
- Advanced Software Engineering Methodologies 1
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- Clinical Reasoning and Diagnostic Skills 1
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- Software Engineering Research 1
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- Electrolyte and hormonal disorders 1
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- Innovations in Medical Education 1
- Co-authors
- Edward H. ShortliffeJohn KunzRobert J. FallatVictor L. YuA. Carlisle ScottLawrence M. FaganBruce G. BuchananWilliam J. Clancey
- Journals
- Artificial Intelligence (1 paper)American Journal of Health-System Pharmacy (1 paper)International Joint Conference on Artificial Intelligence (1 paper)
- Partner nations
- United States
In The Last Decade
Janice S. Aikins
7 papers receiving 276 citations
Peers
Comparison fields: 5 of 82
- Health Information Management 33
- Artificial Intelligence 196
- Family Practice 11
- Health Informatics 5
- Software 14
Countries citing papers authored by Janice S. Aikins
This map shows the geographic impact of Janice S. Aikins'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 Janice S. Aikins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Janice S. Aikins more than expected).
Fields of papers citing papers by Janice S. Aikins
This network shows the impact of papers produced by Janice S. Aikins. 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 Janice S. Aikins. The network helps show where Janice S. Aikins may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Janice S. Aikins, 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 | 1983 | 130 | |
| 2 | 1983 | 4 | |
| 3 | 1983 | 112 | |
| 4 | Application design: issues in expert system architecture | 1981 | 4 |
| 5 | Representation of control knowledge in expert systems | 1980 | 12 |
| 6 | Prototypes and production rules: a knowledge representation for computer consultations | 1980 | 39 |
| 7 | 1976 | 14 |
About Janice S. Aikins
Janice S. Aikins is a scholar working on Family Practice, Artificial Intelligence and Signal Processing, having authored 7 papers that have together received 315 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (5 papers), Semantic Web and Ontologies (4 papers), Multi-Agent Systems and Negotiation (2 papers), Software Engineering Research (1 paper), Advanced Software Engineering Methodologies (1 paper), Electrolyte and hormonal disorders (1 paper), Clinical Reasoning and Diagnostic Skills (1 paper) and Innovations in Medical Education (1 paper). The work is most often cited by research in Health Information Management (33 citations), Artificial Intelligence (196 citations) and Family Practice (11 citations). Janice S. Aikins has collaborated with scholars based in United States. Frequent co-authors include Edward H. Shortliffe, John Kunz, Robert J. Fallat, Victor L. Yu, A. Carlisle Scott, Lawrence M. Fagan, Bruce G. Buchanan, William J. Clancey, Randall Davis and John F. Hannigan. Their work appears in journals such as Artificial Intelligence, American Journal of Health-System Pharmacy and International Joint Conference on Artificial Intelligence.
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.