M. Taboada

817 citations
27 papers · 446 indexed · 1 hit paper · h-index 9

Impact in

Papers in

M. Taboada

22 papers receiving 412 citations

Hit Papers

AI literacy in K-12: a systematic literature review 2023 · 249 citations
249202320262024202550100150200

Peers

M. Taboada
Comparison fields: 5 of 80
  • Health Informatics 43
  • Computer Science Applications 140
  • Health Information Management 32
  • Safety Research 46
  • Artificial Intelligence 168
Replace Gökhan Akçapınar with:
Gökhan Akçapınar Türkiye
Yeonju Jang South Korea
Tatsunori Matsui Japan
Salmiza Saleh Malaysia
Seongyune Choi South Korea
Soohyun Nam Liao United States
Elif Polat Türkiye
Amr M. Mohamed Saudi Arabia
Sinan Hopcan Türkiye
Arne Bewersdorff Germany
M. Taboada relative to Gökhan Akçapınar Türkiye Gökhan Akçapınar's profile →
Citations per field
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Gökhan Akçapınar · 1×
Citations per year

Countries citing papers authored by M. Taboada

Since Specialization
Citations

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

Fields of papers citing papers by M. Taboada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1
AI literacy in K-12: a systematic literature review
Hit paper breakdown →
2023249
2 202040
3 201226
4 201424
5 200916
6 200515
7 201412
8 201310
9 201710
10 20018
11 20127
12 20117
13 19934
14 19994
15 19923
16 20252
17 20112
18
Using lexical, terminological and ontological resources for entity recognition tasks in the medical domain
20081
19
A use case for DAML+OIL: a knowledge base in a clinical domain.
20021
20 20171

About M. Taboada

M. Taboada is a scholar working on Artificial Intelligence, Molecular Biology, Genetics, Health Information Management and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 446 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (17 papers), Semantic Web and Ontologies (16 papers), Natural Language Processing Techniques (7 papers), AI-based Problem Solving and Planning (5 papers), Genomics and Rare Diseases (4 papers), Context-Aware Activity Recognition Systems (2 papers), Electronic Health Records Systems (2 papers) and Usability and User Interface Design (2 papers). The work is most often cited by research in Health Informatics (43 citations), Computer Science Applications (140 citations), Health Information Management (32 citations), Safety Research (46 citations) and Artificial Intelligence (168 citations). M. Taboada has collaborated with scholars based in Spain, Germany and Chile. Frequent co-authors include Lorena Casal Otero, Senén Barro, Carmen Fernández-Morante, Alejandro Catalá, Beatriz Cebreiro López, José Mira, M.J. Sobrido, Sara Cruz, Célia Sofia Moreira and María Pardo. Their work appears in journals such as Journal of Medical Systems, BMC Medical Informatics and Decision Making, Artificial Intelligence in Medicine, Database and International Journal of Human-Computer Studies.

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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