Heather S. Haeberle
- Surgery top 2%
- Health Informatics top 0.1%
- Biomedical Engineering top 10%
- Cardiology and Cardiovascular Medicine top 10%
- Epidemiology
- Co-authors
- Prem N. RamkumarSergio M. NavarroJaret M. KarnutaViktor E. KrebsJonathan L. SchafferBrendan M. PattersonMichael A. MontJ. Matthew Helm
- Topics
- Total Knee Arthroplasty Outcomes (22 papers)Orthopaedic implants and arthroplasty (20 papers)Shoulder Injury and Treatment (12 papers)
- Journals
- SHILAP Revista de lepidopterologíaSpineThe American Journal of Sports Medicine
- Partner nations
- United StatesUnited KingdomArgentina
In The Last Decade
Heather S. Haeberle
65 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Surgery 1.2k
- Health Informatics 521
- Biomedical Engineering 357
- Cardiology and Cardiovascular Medicine 293
- Epidemiology 224
Countries citing papers authored by Heather S. Haeberle
This map shows the geographic impact of Heather S. Haeberle'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 Heather S. Haeberle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Heather S. Haeberle more than expected).
Fields of papers citing papers by Heather S. Haeberle
This network shows the impact of papers produced by Heather S. Haeberle. 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 Heather S. Haeberle. The network helps show where Heather S. Haeberle may publish in the future.
Co-authorship network of co-authors of Heather S. Haeberle
This figure shows the co-authorship network connecting the top 25 collaborators of Heather S. Haeberle. A scholar is included among the top collaborators of Heather S. Haeberle 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 Heather S. Haeberle. Heather S. Haeberle is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 20 | |
| 2 | 5 | |
| 3 | 26 | |
| 4 | Machine Learning and Artificial Intelligence: Definitions, Applications, and Future Directionsbreakdown → | 384 |
| 5 | 75 | |
| 6 | 46 | |
| 7 | 15 | |
| 8 | 28 | |
| 9 | 141 | |
| 10 | 55 | |
| 11 | 23 | |
| 12 | 109 | |
| 13 | 119 | |
| 14 | 7 | |
| 15 | 43 | |
| 16 | 32 | |
| 17 | The Medtech Innovation Course: Description and Initial Experiences with a Novel Collaborative Course Model | 1 |
| 18 | 46 | |
| 19 | 36 | |
| 20 | 22 |
About Heather S. Haeberle
Heather S. Haeberle is a scholar working on Health Informatics, Surgery and Rehabilitation, having authored 67 papers that have together received 2.3k indexed citations. Recurring topics across this work include Total Knee Arthroplasty Outcomes (22 papers), Orthopaedic implants and arthroplasty (20 papers) and Shoulder Injury and Treatment (12 papers). The work is most often cited by research in Health Informatics (521 citations), Surgery (1.2k citations) and Orthopedics and Sports Medicine (180 citations). Heather S. Haeberle has collaborated with scholars based in United States, United Kingdom and Argentina. Frequent co-authors include Prem N. Ramkumar, Sergio M. Navarro, Jaret M. Karnuta, Viktor E. Krebs, Jonathan L. Schaffer, Brendan M. Patterson, Michael A. Mont, J. Matthew Helm, Michael A. Mont and Andrew Swiergosz. Their work appears in journals such as SHILAP Revista de lepidopterología, Spine and The American Journal of Sports Medicine.
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.