Laura Heitsch
Impact in
- Rehabilitation top 5%
- Stroke Rehabilitation and Recovery
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
Papers in
- Epidemiology 19
- Acute Ischemic Stroke Management 19
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- Cerebrovascular and Carotid Artery Diseases 8
- Co-authors
- Jin‐Moo Lee (16 shared papers)Rajat Dhar (11 shared papers)Yasheng Chen (11 shared papers)Andria L. Ford (5 shared papers)Daniel Strbian (7 shared papers)Hongyu An (3 shared papers)Peter D. Panagos (3 shared papers)Agnieszka Słowik (5 shared papers)
- Journals
- Stroke (6 papers)Neurocritical Care (4 papers)Academic Emergency Medicine (2 papers)Journal of Cerebral Blood Flow & Metabolism (2 papers)Neurology (1 paper)
- Partner nations
- United StatesPolandFinland
In The Last Decade
Laura Heitsch
25 papers receiving 428 citations
Peers
Comparison fields: 5 of 63
- Rehabilitation 64
- Health Informatics 13
- Epidemiology 216
- Neurology 49
- Neurology 80
Countries citing papers authored by Laura Heitsch
This map shows the geographic impact of Laura Heitsch'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 Laura Heitsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Laura Heitsch more than expected).
Fields of papers citing papers by Laura Heitsch
This network shows the impact of papers produced by Laura Heitsch. 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 Laura Heitsch. The network helps show where Laura Heitsch may publish in the future.
Co-authors
The 25 scholars most cited alongside Laura Heitsch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 47 | |
| 2 | 2013 | 43 | |
| 3 | 2019 | 39 | |
| 4 | 2015 | 35 | |
| 5 | 2019 | 30 | |
| 6 | 2016 | 28 | |
| 7 | 2021 | 27 | |
| 8 | 2021 | 22 | |
| 9 | 2020 | 21 | |
| 10 | 2020 | 17 | |
| 11 | 2021 | 15 | |
| 12 | 2016 | 14 | |
| 13 | 2019 | 13 | |
| 14 | 2010 | 13 | |
| 15 | 2022 | 11 | |
| 16 | 2007 | 9 | |
| 17 | 2012 | 9 | |
| 18 | 2019 | 8 | |
| 19 | 2014 | 8 | |
| 20 | 2022 | 7 |
About Laura Heitsch
Laura Heitsch is a scholar working on Epidemiology, Pulmonary and Respiratory Medicine, Neurology, Rehabilitation and Internal Medicine, having authored 26 papers that have together received 432 indexed citations. Recurring topics across this work include Acute Ischemic Stroke Management (19 papers), Cerebrovascular and Carotid Artery Diseases (8 papers), Traumatic Brain Injury and Neurovascular Disturbances (4 papers), Stroke Rehabilitation and Recovery (3 papers), Venous Thromboembolism Diagnosis and Management (2 papers), Intracerebral and Subarachnoid Hemorrhage Research (2 papers), Epigenetics and DNA Methylation (1 paper) and Medical Image Segmentation Techniques (1 paper). The work is most often cited by research in Rehabilitation (64 citations), Health Informatics (13 citations), Epidemiology (216 citations), Neurology (49 citations) and Neurology (80 citations). Laura Heitsch has collaborated with scholars based in United States, Poland and Finland. Frequent co-authors include Jin‐Moo Lee, Rajat Dhar, Yasheng Chen, Andria L. Ford, Daniel Strbian, Hongyu An, Peter D. Panagos, Agnieszka Słowik, Israel Fernández‐Cadenas and Caty Carrera. Their work appears in journals such as Stroke, Neurocritical Care, Academic Emergency Medicine, Journal of Cerebral Blood Flow & Metabolism and Neurology.
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.