Alejandro Cosa‐Linan

1.3k citations
13 papers · 748 · 1 hit paper · h-index 11

Impact in

Papers in

Alejandro Cosa‐Linan

13 papers receiving 742 citations

Alejandro Cosa‐Linan's Hit Papers

Transfer learning for medical image classification: a literature review 2022 · 497 citations
4970+1+2Years since publication100200300400

Peers

Alejandro Cosa‐Linan
Comparison fields: 5 of 122
  • Health Informatics 39
  • Biological Psychiatry 40
  • Radiology, Nuclear Medicine and Imaging 208
  • Neurology 61
  • Cellular and Molecular Neuroscience 103
Replace Qingyu Zhao with:
Qingyu Zhao United States
Francesca Gallivanone Italy
Giorgia Grisot United States
Alberto Redolfi Italy
Hyun‐Jong Jang South Korea
Peijun Wang China
Hailong Li United States
Xiaoli Liu China
Alessia Sarica Italy
Walter Hugo Lopez Pinaya United Kingdom
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Countries citing papers authored by Alejandro Cosa‐Linan

Since Specialization
Citations

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

Fields of papers citing papers by Alejandro Cosa‐Linan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alejandro Cosa‐Linan. 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 Alejandro Cosa‐Linan. The network helps show where Alejandro Cosa‐Linan may publish in the future.

Co-authors

The 25 scholars most cited alongside Alejandro Cosa‐Linan, 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 Alejandro Cosa‐Linan Line = papers co-authored together Alejandro Cosa‐Linan links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1
Transfer learning for medical image classification: a literature review
Hit paper breakdown →
2022497
2 201952
3 202041
4 201733
5 201925
6 201824
7 201715
8 201715
9 202213
10 201712
11 202011
12 20208
13 20212

About Alejandro Cosa‐Linan

Alejandro Cosa‐Linan is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience, Biological Psychiatry, Pharmacology and Radiology, Nuclear Medicine and Imaging, having authored 13 papers that have together received 748 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (4 papers), Functional Brain Connectivity Studies (4 papers), Tryptophan and brain disorders (3 papers), Neurotransmitter Receptor Influence on Behavior (3 papers), Neural dynamics and brain function (2 papers), Treatment of Major Depression (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper) and Biochemical effects in animals (1 paper). The work is most often cited by research in Health Informatics (39 citations), Biological Psychiatry (40 citations), Radiology, Nuclear Medicine and Imaging (208 citations), Neurology (61 citations) and Cellular and Molecular Neuroscience (103 citations). Alejandro Cosa‐Linan has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Kim Eun Hee, Nandhini Santhanam, Máté E. Maros, Thomas Ganslandt, Mahboubeh Jannesari, Rainer Spanagel, Wolfgang Weber‐Fahr, Silvia De Santis, Roberto Ciccocioppo and Robert E. Becker. Their work appears in journals such as Translational Psychiatry, Scientific Reports, Frontiers in Psychiatry, International Journal of Molecular Sciences and JAMA Psychiatry.

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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