Annie Gu
Impact in
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- ECG Monitoring and Analysis
- Cardiac electrophysiology and arrhythmias
- Heart Rate Variability and Autonomic Control
- Atrial Fibrillation Management and Outcomes
- Cognitive Neuroscience top 5%
- EEG and Brain-Computer Interfaces
Papers in ⓘ
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- Nursing Diagnosis and Documentation 1
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- ECG Monitoring and Analysis 5
- Cardiac electrophysiology and arrhythmias 4
- Heart Rate Variability and Autonomic Control 1
- Co-authors
- Andoni Elola (6 shared papers)Ali Bahrami Rad (7 shared papers)Matthew A. Reyna (6 shared papers)Erick Andres Perez Alday (7 shared papers)Gari D. Clifford (6 shared papers)Ashish Sharma (5 shared papers)Salman Seyedi (4 shared papers)Chad Robichaux (3 shared papers)
- Journals
- Physiological Measurement (2 papers)Journal of Electrocardiology (1 paper)SHILAP Revista de lepidopterología (1 paper)Computing in cardiology (2 papers)
- Partner nations
- United StatesSpainPortugal
In The Last Decade
Annie Gu
7 papers receiving 545 citations
Hit Papers
Peers
Comparison fields: 5 of 42
- Cardiology and Cardiovascular Medicine 486
- Cognitive Neuroscience 288
- Health Informatics 8
- Pulmonary and Respiratory Medicine 194
- Artificial Intelligence 93
Countries citing papers authored by Annie Gu
This map shows the geographic impact of Annie Gu'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 Annie Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Annie Gu more than expected).
Fields of papers citing papers by Annie Gu
This network shows the impact of papers produced by Annie Gu. 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 Annie Gu. The network helps show where Annie Gu may publish in the future.
Co-authors
The 25 scholars most cited alongside Annie Gu, 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 | Classification of 12-lead ECGs: the PhysioNet/Computing in Cardiology Challenge 2020 Hit paper breakdown → | 2020 | 294 |
| 2 | Will Two Do? Varying Dimensions in Electrocardiography: The PhysioNet/Computing in Cardiology Challenge 2021 Hit paper breakdown → | 2021 | 131 |
| 3 | 2020 | 53 | |
| 4 | 2023 | 41 | |
| 5 | 2022 | 26 | |
| 6 | 2022 | 7 | |
| 7 | 2022 | 7 |
About Annie Gu
Annie Gu is a scholar working on Issues, ethics and legal aspects, Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine, Infectious Diseases and Organic Chemistry, having authored 7 papers that have together received 559 indexed citations. Recurring topics across this work include Phonocardiography and Auscultation Techniques (7 papers), ECG Monitoring and Analysis (5 papers), Cardiac electrophysiology and arrhythmias (4 papers), Heart Rate Variability and Autonomic Control (1 paper) and Nursing Diagnosis and Documentation (1 paper). The work is most often cited by research in Cardiology and Cardiovascular Medicine (486 citations), Cognitive Neuroscience (288 citations), Health Informatics (8 citations), Pulmonary and Respiratory Medicine (194 citations) and Artificial Intelligence (93 citations). Annie Gu has collaborated with scholars based in United States, Spain and Portugal. Frequent co-authors include Andoni Elola, Ali Bahrami Rad, Matthew A. Reyna, Erick Andres Perez Alday, Gari D. Clifford, Ashish Sharma, Salman Seyedi, Chad Robichaux, Amit Shah and Chengyu Liu. Their work appears in journals such as Physiological Measurement, Journal of Electrocardiology, SHILAP Revista de lepidopterología and Computing in cardiology.
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.