Jeffrey G. Klann

2.8k citations
34 papers · 533 indexed · h-index 16
Topics
Electronic Health Records Systems (17 papers)Biomedical Text Mining and Ontologies (11 papers)Machine Learning in Healthcare (8 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEJournal of Medical Internet Research

In The Last Decade

Jeffrey G. Klann

34 papers receiving 516 citations

Peers

Jeffrey G. Klann
Comparison fields: 5 of 93
  • Health Information Management 235
  • Artificial Intelligence 205
  • Molecular Biology 112
  • Epidemiology 78
  • Public Health, Environmental and Occupational Health 71
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Citations per field
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Citations per year

Countries citing papers authored by Jeffrey G. Klann

Since Specialization
Citations

This map shows the geographic impact of Jeffrey G. Klann'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 Jeffrey G. Klann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey G. Klann more than expected).

Fields of papers citing papers by Jeffrey G. Klann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey G. Klann. 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 Jeffrey G. Klann. The network helps show where Jeffrey G. Klann may publish in the future.

Co-authorship network of co-authors of Jeffrey G. Klann

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey G. Klann. A scholar is included among the top collaborators of Jeffrey G. Klann 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 Jeffrey G. Klann. Jeffrey G. Klann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 2
3 19
4 24
5 15
6 11
7 23
8 32
9 57
10
The Scalable Collaborative Infrastructure for a Learning Health System.
1
11
Query Health Across Communities: The New York City Department of Health and Mental Hygiene Pilot.
1
12
Query Health: One Step Toward a Learning Health System.
1
13
Decision support from local data: Creating adaptive order menus from past clinician behavior
11
14
Patient-tailored prioritization for a pediatric care decision support system through machine learning
1
15 14
16 19
17 33
18 19
19
Query Health and i2b2: Enabling Standards-based, Multiplatform Population Health Queries.
1
20 34

About Jeffrey G. Klann

Jeffrey G. Klann is a scholar working on Health Information Management, Issues, ethics and legal aspects and Health Informatics, having authored 34 papers that have together received 533 indexed citations. Recurring topics across this work include Electronic Health Records Systems (17 papers), Biomedical Text Mining and Ontologies (11 papers) and Machine Learning in Healthcare (8 papers). The work is most often cited by research in Health Information Management (235 citations), Health Informatics (53 citations) and Issues, ethics and legal aspects (24 citations). Jeffrey G. Klann has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Shawn N. Murphy, Peter Szolovits, Gunther Schadow, Hossein Estiri, Kenneth D. Mandl, Stephen M. Downs, Stephen M. Downs, Kavishwar B. Wagholikar, Vibha Anand and Marc D. Natter. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Medical Internet Research.

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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