Marta Garnelo
Impact in
-
- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- Immune cells in cancer
- Hepatology top 10%
- Hepatocellular Carcinoma Treatment and Prognosis
Papers in
-
- Topic Modeling 2
- Natural Language Processing Techniques 1
- Neural Networks and Applications 1
- Co-authors
- Murray Shanahan (1 shared paper)Alexander Yaw Fui Chung (1 shared paper)Chun Jye Lim (1 shared paper)Zhisheng Her (1 shared paper)Achim Weber (1 shared paper)Mathias Heikenwälder (1 shared paper)Jinmiao Chen (1 shared paper)Alex Y. Tan (1 shared paper)
- Journals
- Gut (1 paper)Scientific Reports (1 paper)Current Opinion in Behavioral Sciences (1 paper)Inter-American Development Bank eBooks (1 paper)UCL Discovery (University College London) (1 paper)
- Partner nations
- United KingdomUnited StatesSlovakia
In The Last Decade
Marta Garnelo
7 papers receiving 481 citations
Peers
Comparison fields: 5 of 105
- Immunology 177
- Hepatology 66
- Oncology 209
- Health Informatics 7
- Cancer Research 63
Countries citing papers authored by Marta Garnelo
This map shows the geographic impact of Marta Garnelo'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 Marta Garnelo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marta Garnelo more than expected).
Fields of papers citing papers by Marta Garnelo
This network shows the impact of papers produced by Marta Garnelo. 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 Marta Garnelo. The network helps show where Marta Garnelo may publish in the future.
Co-authors
The 25 scholars most cited alongside Marta Garnelo, 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 | 2015 | 358 | |
| 2 | 2019 | 117 | |
| 3 | 2022 | 10 | |
| 4 | 2021 | 4 | |
| 5 | 2019 | 4 | |
| 6 | Open-ended learning in symmetric zero-sum games | 2019 | 2 |
| 7 | 2021 | 2 |
About Marta Garnelo
Marta Garnelo is a scholar working on Artificial Intelligence, Automotive Engineering, Health, Clinical Psychology and Sociology and Political Science, having authored 7 papers that have together received 497 indexed citations. Recurring topics across this work include Topic Modeling (2 papers), Resilience and Mental Health (1 paper), Natural Language Processing Techniques (1 paper), Time Series Analysis and Forecasting (1 paper), Multimodal Machine Learning Applications (1 paper), Neural Networks and Applications (1 paper), Experimental Behavioral Economics Studies (1 paper) and Immunotherapy and Immune Responses (1 paper). The work is most often cited by research in Immunology (177 citations), Hepatology (66 citations), Oncology (209 citations), Health Informatics (7 citations) and Cancer Research (63 citations). Marta Garnelo has collaborated with scholars based in United Kingdom, United States and Slovakia. Frequent co-authors include Murray Shanahan, Alexander Yaw Fui Chung, Chun Jye Lim, Zhisheng Her, Achim Weber, Mathias Heikenwälder, Jinmiao Chen, Alex Y. Tan, Joe Yeong and Han Chong Toh. Their work appears in journals such as Gut, Scientific Reports, Current Opinion in Behavioral Sciences, Inter-American Development Bank eBooks and UCL Discovery (University College London).
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.