Andrew Jesson
Impact in
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- Infection Control in Healthcare
Papers in
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- Explainable Artificial Intelligence (XAI) 2
- Domain Adaptation and Few-Shot Learning 1
- Machine Learning in Healthcare 1
- Machine Learning and Data Classification 1
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- Infection Control in Healthcare 2
- Co-authors
- Marin L. Schweizer (2 shared papers)Eli N. Perencevich (2 shared papers)Graeme N. Forrest (2 shared papers)Heather Schacht Reisinger (2 shared papers)İpek Oğuz (1 shared paper)Jacob C. Reinhold (1 shared paper)Ciprian M. Crainiceanu (1 shared paper)Jerry L. Prince (1 shared paper)
- Journals
- Scientific Reports (1 paper)Infection Control and Hospital Epidemiology (1 paper)American Journal of Infection Control (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesCanadaIsrael
In The Last Decade
Andrew Jesson
6 papers receiving 196 citations
Peers
Comparison fields: 5 of 95
- General Dentistry 8
- Infectious Diseases 54
- Health Informatics 3
- Radiology, Nuclear Medicine and Imaging 48
- Applied Microbiology and Biotechnology 4
Countries citing papers authored by Andrew Jesson
This map shows the geographic impact of Andrew Jesson'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 Andrew Jesson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Jesson more than expected).
Fields of papers citing papers by Andrew Jesson
This network shows the impact of papers produced by Andrew Jesson. 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 Andrew Jesson. The network helps show where Andrew Jesson may publish in the future.
Co-authors
The 25 scholars most cited alongside Andrew Jesson, 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 | 2020 | 120 | |
| 2 | 2014 | 32 | |
| 3 | 2016 | 26 | |
| 4 | Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification | 2018 | 15 |
| 5 | Improving Deterministic Uncertainty Estimation in Deep Learning for Classification and Regression. | 2021 | 7 |
| 6 | Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models | 2020 | 3 |
| 7 | 2024 | 0 | |
| 8 | 2024 | 0 |
About Andrew Jesson
Andrew Jesson is a scholar working on Artificial Intelligence, Infectious Diseases, Pulmonary and Respiratory Medicine, Food Science and Molecular Biology, having authored 8 papers that have together received 203 indexed citations. Recurring topics across this work include Infection Control and Ventilation (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Food Safety and Hygiene (2 papers), Infection Control in Healthcare (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Systemic Lupus Erythematosus Research (1 paper), Machine Learning in Healthcare (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in General Dentistry (8 citations), Infectious Diseases (54 citations), Health Informatics (3 citations), Radiology, Nuclear Medicine and Imaging (48 citations) and Applied Microbiology and Biotechnology (4 citations). Andrew Jesson has collaborated with scholars based in United States, Canada and Israel. Frequent co-authors include Marin L. Schweizer, Eli N. Perencevich, Graeme N. Forrest, Heather Schacht Reisinger, İpek Oğuz, Jacob C. Reinhold, Ciprian M. Crainiceanu, Jerry L. Prince, Snehashis Roy and Mohsen Ghafoorian. Their work appears in journals such as Scientific Reports, Infection Control and Hospital Epidemiology, American Journal of Infection Control and arXiv (Cornell University).
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.