Pablo Messina
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Image Retrieval and Classification Techniques
- Multimodal Machine Learning Applications
Papers in
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- Image Retrieval and Classification Techniques 4
- Visual Attention and Saliency Detection 4
- Multimodal Machine Learning Applications 2
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- Aesthetic Perception and Analysis 4
- Co-authors
- Denis Parra (9 shared papers)Vicente Domı́nguez (4 shared papers)Álvaro Soto (3 shared papers)Christoph Trattner (2 shared papers)Cecilia Besa (1 shared paper)Cristián Tejos (1 shared paper)Marcelo E. Andía (1 shared paper)Claudia Prieto (1 shared paper)
- Journals
- Earth-Science Reviews (1 paper)User Modeling and User-Adapted Interaction (1 paper)ACM Computing Surveys (1 paper)ACM Transactions on Interactive Intelligent Systems (1 paper)Conference on Recommender Systems (2 papers)
In The Last Decade
Pablo Messina
11 papers receiving 134 citations
Peers
Comparison fields: 5 of 51
- Health Informatics 20
- Computer Vision and Pattern Recognition 54
- Artificial Intelligence 83
- Computer Graphics and Computer-Aided Design 6
- General Decision Sciences 3
Countries citing papers authored by Pablo Messina
This map shows the geographic impact of Pablo Messina'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 Pablo Messina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pablo Messina more than expected).
Fields of papers citing papers by Pablo Messina
This network shows the impact of papers produced by Pablo Messina. 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 Pablo Messina. The network helps show where Pablo Messina may publish in the future.
Co-authors
The 12 scholars most cited alongside Pablo Messina, 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 | 2022 | 46 | |
| 2 | 2018 | 42 | |
| 3 | 2019 | 30 | |
| 4 | 2020 | 8 | |
| 5 | 2005 | 6 | |
| 6 | Anaglyph Image Technology As a Visualization Tool for Teaching Geology of National Parks | 2003 | 2 |
| 7 | 2024 | 1 | |
| 8 | Towards Explanations for Visual Recommender Systems of Artistic Images. | 2018 | 1 |
| 9 | PUC Chile team at VQA-Med 2021: approaching VQA as a classification task via fine-tuning a pretrained CNN. | 2021 | 1 |
| 10 | CuratorNet: Visually-aware Recommendation of Art Images | 2020 | 1 |
| 11 | 2024 | 1 |
About Pablo Messina
Pablo Messina is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Molecular Biology, having authored 11 papers that have together received 139 indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (4 papers), Visual Attention and Saliency Detection (4 papers), Aesthetic Perception and Analysis (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Multimodal Machine Learning Applications (2 papers), Topic Modeling (2 papers), Natural Language Processing Techniques (1 paper) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Health Informatics (20 citations), Computer Vision and Pattern Recognition (54 citations), Artificial Intelligence (83 citations), Computer Graphics and Computer-Aided Design (6 citations) and General Decision Sciences (3 citations). Pablo Messina has collaborated with scholars based in Chile, Australia and Norway. Frequent co-authors include Denis Parra, Vicente Domı́nguez, Álvaro Soto, Christoph Trattner, Cecilia Besa, Cristián Tejos, Marcelo E. Andía, Claudia Prieto, Sergio Uribe and Daniel Capurro. Their work appears in journals such as Earth-Science Reviews, User Modeling and User-Adapted Interaction, ACM Computing Surveys, ACM Transactions on Interactive Intelligent Systems and Conference on Recommender Systems.
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.