Ignacio Molina
Impact in
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- Artificial Intelligence in Healthcare
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
Papers in
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- Neural Networks and Applications 2
- AI in cancer detection 2
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- Statistical Methods and Inference 2
- Co-authors
- José Manuel Jerez Aragonés (6 shared papers)Leonardo Oliveira Franco (6 shared papers)Emilio Alba Conejo (2 shared papers)Nuria Ribelles (1 shared paper)Pedro J. García-Laencina (1 shared paper)M Casado Martín (1 shared paper)Francisco Ortega-Zamorano (2 shared papers)Timothy J. Richards (2 shared papers)
- Journals
- Artificial Intelligence in Medicine (1 paper)Electronics Letters (1 paper)Agribusiness (1 paper)Engineering Applications of Artificial Intelligence (1 paper)Data (2 papers)
- Partner nations
- SpainUnited StatesGermany
In The Last Decade
Ignacio Molina
14 papers receiving 549 citations
Peers
Comparison fields: 5 of 119
- Health Information Management 69
- Statistics and Probability 68
- Artificial Intelligence 252
- Computational Mathematics 3
- Health Informatics 4
Countries citing papers authored by Ignacio Molina
This map shows the geographic impact of Ignacio Molina'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 Ignacio Molina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ignacio Molina more than expected).
Fields of papers citing papers by Ignacio Molina
This network shows the impact of papers produced by Ignacio Molina. 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 Ignacio Molina. The network helps show where Ignacio Molina may publish in the future.
Co-authors
The 25 scholars most cited alongside Ignacio Molina, 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 | 2010 | 452 | |
| 2 | Missing data imputation in breast cancer prognosis | 2006 | 25 |
| 3 | 2014 | 23 | |
| 4 | 2013 | 12 | |
| 5 | 2007 | 12 | |
| 6 | 2006 | 11 | |
| 7 | 2010 | 10 | |
| 8 | 2006 | 7 | |
| 9 | 2005 | 6 | |
| 10 | 2013 | 4 | |
| 11 | 2009 | 4 | |
| 12 | 2004 | 2 | |
| 13 | 2013 | 1 | |
| 14 | 2020 | 1 | |
| 15 | 2000 | 1 | |
| 16 | 2025 | 1 | |
| 17 | 2009 | 1 | |
| 18 | 2025 | 0 |
About Ignacio Molina
Ignacio Molina is a scholar working on Artificial Intelligence, Statistics and Probability, Marketing, Tourism, Leisure and Hospitality Management and Instrumentation, having authored 18 papers that have together received 573 indexed citations. Recurring topics across this work include High voltage insulation and dielectric phenomena (2 papers), Sensor Technology and Measurement Systems (2 papers), Neural Networks and Applications (2 papers), Organic Food and Agriculture (2 papers), Gene expression and cancer classification (2 papers), Statistical Methods and Inference (2 papers), Consumer Market Behavior and Pricing (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Information Management (69 citations), Statistics and Probability (68 citations), Artificial Intelligence (252 citations), Computational Mathematics (3 citations) and Health Informatics (4 citations). Ignacio Molina has collaborated with scholars based in Spain, United States and Germany. Frequent co-authors include José Manuel Jerez Aragonés, Leonardo Oliveira Franco, Emilio Alba Conejo, Nuria Ribelles, Pedro J. García-Laencina, M Casado Martín, Francisco Ortega-Zamorano, Timothy J. Richards, Rajeswari Sundararajan and Ram N. Acharya. Their work appears in journals such as Artificial Intelligence in Medicine, Electronics Letters, Agribusiness, Engineering Applications of Artificial Intelligence and Data.
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.