Julia Ive
Impact in
- Health Informatics top 10%
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Machine Learning in Healthcare
- Sentiment Analysis and Opinion Mining
Papers in
-
- Topic Modeling 16
- Natural Language Processing Techniques 10
- Machine Learning in Healthcare 9
- Sentiment Analysis and Opinion Mining 2
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- Biomedical Text Mining and Ontologies 8
- Co-authors
- Lucia Specia (8 shared papers)Sumithra Velupillai (5 shared papers)Pranava Madhyastha (2 shared papers)Rina Dutta (1 shared paper)George Gkotsis (1 shared paper)Robert C. Stewart (1 shared paper)Frédéric Blain (2 shared papers)Stephen Puntis (1 shared paper)
- Journals
- Computational Linguistics (2 papers)Language Resources and Evaluation (2 papers)npj Digital Medicine (2 papers)Experimental Biology and Medicine (1 paper)Clinical Epidemiology (1 paper)
- Partner nations
- United KingdomSwedenFrance
In The Last Decade
Julia Ive
25 papers receiving 221 citations
Peers
Comparison fields: 5 of 55
- Health Informatics 17
- Artificial Intelligence 186
- Applied Psychology 25
- Computer Vision and Pattern Recognition 53
- Health Information Management 12
Countries citing papers authored by Julia Ive
This map shows the geographic impact of Julia Ive'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 Julia Ive with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julia Ive more than expected).
Fields of papers citing papers by Julia Ive
This network shows the impact of papers produced by Julia Ive. 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 Julia Ive. The network helps show where Julia Ive may publish in the future.
Co-authors
The 25 scholars most cited alongside Julia Ive, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 51 | |
| 2 | 2020 | 47 | |
| 3 | 2018 | 42 | |
| 4 | Exploring Transformer Text Generation for Medical Dataset Augmentation. | 2020 | 21 |
| 5 | deepQuest: A Framework for Neural-based Quality Estimation | 2018 | 15 |
| 6 | 2023 | 8 | |
| 7 | 2021 | 5 | |
| 8 | 2018 | 5 | |
| 9 | 2024 | 4 | |
| 10 | 2022 | 4 | |
| 11 | 2022 | 4 | |
| 12 | 2022 | 4 | |
| 13 | 2022 | 4 | |
| 14 | A Post-Editing Dataset in the Legal Domain: Do we Underestimate Neural Machine Translation Quality? | 2020 | 3 |
| 15 | 2019 | 3 | |
| 16 | 2020 | 3 | |
| 17 | KCL-Health-NLP@CLEF eHealth 2018 Task 1 : ICD-10 coding of French and Italian death certificates with character-level convolutional neural networks | 2018 | 3 |
| 18 | 2024 | 2 | |
| 19 | 2024 | 1 | |
| 20 | 2025 | 1 |
About Julia Ive
Julia Ive is a scholar working on Artificial Intelligence, Molecular Biology, Health Informatics, Social Psychology and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 235 indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Natural Language Processing Techniques (10 papers), Machine Learning in Healthcare (9 papers), Biomedical Text Mining and Ontologies (8 papers), Artificial Intelligence in Healthcare and Education (3 papers), Mental Health via Writing (2 papers), Multimodal Machine Learning Applications (2 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Health Informatics (17 citations), Artificial Intelligence (186 citations), Applied Psychology (25 citations), Computer Vision and Pattern Recognition (53 citations) and Health Information Management (12 citations). Julia Ive has collaborated with scholars based in United Kingdom, Sweden and France. Frequent co-authors include Lucia Specia, Sumithra Velupillai, Pranava Madhyastha, Rina Dutta, George Gkotsis, Robert C. Stewart, Frédéric Blain, Stephen Puntis, Angus Roberts and Robert Stewart. Their work appears in journals such as Computational Linguistics, Language Resources and Evaluation, npj Digital Medicine, Experimental Biology and Medicine and Clinical Epidemiology.
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.