Ignacio Molina
- Artificial Intelligence top 10%
- Health Information Management top 2%
- Statistics and Probability top 5%
- Information Systems top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- José M. JerezLeonardo FrancoPedro J. García-LaencinaEmilio AlbaNuria RibellesMiguel MartínR. SundararajanTimothy J. Richards
- Topics
- Statistical Methods and Inference (2 papers)High voltage insulation and dielectric phenomena (2 papers)Statistical Methods and Bayesian Inference (1 paper)
- Journals
- Electronics LettersEngineering Applications of Artificial IntelligenceArtificial Intelligence in Medicine
- Partner nations
- United StatesSpainChile
In The Last Decade
Ignacio Molina
11 papers receiving 445 citations
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 199
- Health Information Management 64
- Statistics and Probability 64
- Information Systems 56
- Computer Vision and Pattern Recognition 51
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-authorship network of co-authors of Ignacio Molina
This figure shows the co-authorship network connecting the top 25 collaborators of Ignacio Molina. A scholar is included among the top collaborators of Ignacio Molina based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ignacio Molina. Ignacio Molina is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 21 | |
| 6 | 1 | |
| 7 | 12 | |
| 8 | 374 | |
| 9 | 10 | |
| 10 | 1 | |
| 11 | Missing data imputation in breast cancer prognosis | 23 |
| 12 | 7 | |
| 13 | 10 | |
| 14 | 6 | |
| 15 | 1 |
About Ignacio Molina
Ignacio Molina is a scholar working on Tourism, Leisure and Hospitality Management, Instrumentation and Development, having authored 15 papers that have together received 467 indexed citations. Recurring topics across this work include Statistical Methods and Inference (2 papers), High voltage insulation and dielectric phenomena (2 papers) and Statistical Methods and Bayesian Inference (1 paper). The work is most often cited by research in Health Information Management (64 citations), Statistics and Probability (64 citations) and Artificial Intelligence (199 citations). Ignacio Molina has collaborated with scholars based in United States, Spain and Chile. Frequent co-authors include José M. Jerez, Leonardo Franco, Pedro J. García-Laencina, Emilio Alba, Nuria Ribelles, Miguel Martín, R. Sundararajan, Timothy J. Richards, Francisco Ortega-Zamorano and Ram N. Acharya. Their work appears in journals such as Electronics Letters, Engineering Applications of Artificial Intelligence and Artificial Intelligence in Medicine.
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.