David J. Albers
- Artificial Intelligence top 2%
- Health Information Management top 0.2%
- Molecular Biology
- Endocrinology, Diabetes and Metabolism top 5%
- Epidemiology top 10%
- Co-authors
- George HripcsakLena MamykinaMatthew E. LevineGunnar HartvigsenEirik ÅrsandAshenafi Zebene WoldaregayTaxiarchis BotsisJ. C. Sprott
- Topics
- Diabetes Management and Research (21 papers)Machine Learning in Healthcare (19 papers)Respiratory Support and Mechanisms (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEAmerican Journal of Psychiatry
- Partner nations
- United StatesGermanyNorway
In The Last Decade
David J. Albers
85 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 161
- Artificial Intelligence 805
- Health Information Management 495
- Molecular Biology 374
- Endocrinology, Diabetes and Metabolism 369
- Epidemiology 359
Countries citing papers authored by David J. Albers
This map shows the geographic impact of David J. Albers'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 David J. Albers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David J. Albers more than expected).
Fields of papers citing papers by David J. Albers
This network shows the impact of papers produced by David J. Albers. 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 David J. Albers. The network helps show where David J. Albers may publish in the future.
Co-authorship network of co-authors of David J. Albers
This figure shows the co-authorship network connecting the top 25 collaborators of David J. Albers. A scholar is included among the top collaborators of David J. Albers 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 David J. Albers. David J. Albers is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 9 | |
| 9 | 9 | |
| 10 | 7 | |
| 11 | 12 | |
| 12 | 3 | |
| 13 | 8 | |
| 14 | 24 | |
| 15 | 7 | |
| 16 | 54 | |
| 17 | 33 | |
| 18 | 114 | |
| 19 | 45 | |
| 20 | Model Selection For EHR Laboratory Tests Preserving Healthcare Context and Underlying Physiology. | 2 |
About David J. Albers
David J. Albers is a scholar working on Health Information Management, Issues, ethics and legal aspects and Critical Care and Intensive Care Medicine, having authored 93 papers that have together received 2.7k indexed citations. Recurring topics across this work include Diabetes Management and Research (21 papers), Machine Learning in Healthcare (19 papers) and Respiratory Support and Mechanisms (9 papers). The work is most often cited by research in Health Information Management (495 citations), Issues, ethics and legal aspects (83 citations) and Health Informatics (81 citations). David J. Albers has collaborated with scholars based in United States, Germany and Norway. Frequent co-authors include George Hripcsak, Lena Mamykina, Matthew E. Levine, Gunnar Hartvigsen, Eirik Årsand, Ashenafi Zebene Woldaregay, Taxiarchis Botsis, J. C. Sprott, Noémie Elhadad and Adler Perotte. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and American Journal of Psychiatry.
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.