Iván Macía

25 papers receiving 268 citations

Peers

Iván Macía
Comparison fields: 5 of 68
  • Radiology, Nuclear Medicine and Imaging 81
  • Computer Vision and Pattern Recognition 69
  • Pulmonary and Respiratory Medicine 108
  • Health Informatics 4
  • Artificial Intelligence 80
Replace Carlos Lima with:
Carlos Lima Portugal
Kristin McLeod Norway
Benoît Presles France
Shifeng Zhao China
Sara El Hadji Italy
Binrong Ma China
Danilo Babin Belgium
Youdan Feng China
Xiaomei Zhu China
Karen López‐Linares Spain
Iván Macía relative to Carlos Lima Portugal Carlos Lima's profile →
Citations per field
00.5×1.5×1.8×
Carlos Lima · 1×
Citations per year

Countries citing papers authored by Iván Macía

Since Specialization
Citations

This map shows the geographic impact of Iván Macía'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 Iván Macía with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iván Macía more than expected).

Fields of papers citing papers by Iván Macía

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Iván Macía. 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 Iván Macía. The network helps show where Iván Macía may publish in the future.

Co-authors

The 25 scholars most cited alongside Iván Macía, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Iván Macía Line = papers co-authored together Iván Macía links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018105
2 201958
3 202012
4 201112
5 202310
6 20049
7 20119
8 20189
9 20196
10 20176
11 20076
12 20045
13 20154
14 20214
15 20084
16 20233
17 20212
18 20212
19 20252
20 20232

About Iván Macía

Iván Macía is a scholar working on Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition, Artificial Intelligence, Cardiology and Cardiovascular Medicine and Biomedical Engineering, having authored 26 papers that have together received 275 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (5 papers), Aortic aneurysm repair treatments (5 papers), AI in cancer detection (4 papers), Virtual Reality Applications and Impacts (3 papers), Biomedical Text Mining and Ontologies (3 papers), Cerebrovascular and Carotid Artery Diseases (3 papers), Clinical practice guidelines implementation (3 papers) and Advanced X-ray and CT Imaging (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (81 citations), Computer Vision and Pattern Recognition (69 citations), Pulmonary and Respiratory Medicine (108 citations), Health Informatics (4 citations) and Artificial Intelligence (80 citations). Iván Macía has collaborated with scholars based in Spain, United Kingdom and Germany. Frequent co-authors include Karen López‐Linares, Miguel Á. González Ballester, Grégory Maclair, Mario Ceresa, Manuel Graña, Hui Wang, Reyer Zwiggelaar, Andrik Rampun, Bryan Scotney and Philip Morrow. Their work appears in journals such as Medical Image Analysis, Frontiers in Bioengineering and Biotechnology, International Journal of Environmental Research and Public Health, Computer Methods and Programs in Biomedicine and Journal of Medical Internet Research.

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.

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