Ignacio Molina
Impact in
-
- Artificial Intelligence in Healthcare
- Statistics and Probability top 5%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
Papers in
- Co-authors
- José M. Jerez (3 shared papers)Leonardo Franco (3 shared papers)Pedro J. García-Laencina (1 shared paper)Miguel Martín (1 shared paper)Nuria Ribelles (1 shared paper)Emilio Alba (1 shared paper)R. Sundararajan (2 shared papers)Timothy J. Richards (2 shared papers)
- Journals
- Engineering Applications of Artificial Intelligence (1 paper)Artificial Intelligence in Medicine (1 paper)Agribusiness (1 paper)Electronics Letters (1 paper)Data (2 papers)
- Partner nations
- United StatesSpainGermany
In The Last Decade
Ignacio Molina
11 papers receiving 458 citations
Peers
Comparison fields: 5 of 117
- Health Information Management 57
- Statistics and Probability 56
- Artificial Intelligence 192
- Computational Mathematics 2
- 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 | 385 | |
| 2 | Missing data imputation in breast cancer prognosis | 2006 | 23 |
| 3 | 2014 | 21 | |
| 4 | 2013 | 12 | |
| 5 | 2010 | 10 | |
| 6 | 2006 | 10 | |
| 7 | 2006 | 7 | |
| 8 | 2005 | 6 | |
| 9 | 2025 | 1 | |
| 10 | 2013 | 1 | |
| 11 | 2000 | 1 | |
| 12 | 2009 | 1 | |
| 13 | 2020 | 0 | |
| 14 | 2025 | 0 |
About Ignacio Molina
Ignacio Molina is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Statistics and Probability, Materials Chemistry and Computer Networks and Communications, having authored 14 papers that have together received 478 indexed citations. Recurring topics across this work include Statistical Methods and Inference (2 papers), High voltage insulation and dielectric phenomena (2 papers), Consumer Market Behavior and Pricing (1 paper), Analytical Chemistry and Sensors (1 paper), Gene expression and cancer classification (1 paper), Medical Image Segmentation Techniques (1 paper), Food Waste Reduction and Sustainability (1 paper) and Microfluidic and Bio-sensing Technologies (1 paper). The work is most often cited by research in Health Information Management (57 citations), Statistics and Probability (56 citations), Artificial Intelligence (192 citations), Computational Mathematics (2 citations) and Health Informatics (4 citations). Ignacio Molina has collaborated with scholars based in United States, Spain and Germany. Frequent co-authors include José M. Jerez, Leonardo Franco, Pedro J. García-Laencina, Miguel Martín, Nuria Ribelles, Emilio Alba, R. Sundararajan, Timothy J. Richards, Francisco Ortega-Zamorano and Ram N. Acharya. Their work appears in journals such as Engineering Applications of Artificial Intelligence, Artificial Intelligence in Medicine, Agribusiness, Electronics Letters 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.