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Tapio Salakoski

Tapio Salakoski

D-Index & Metrics

Computer Science

D-Index
45
Citations
10014
World Ranking
7117
National Ranking
50

Overview

Tapio Salakoski is affiliated with the University of Turku in Finland. Their research primarily spans the field of Computer Science, with significant focus on Artificial Intelligence. Contributions also extend into subfields such as Computer Science Applications, Developmental and Educational Psychology, Molecular Biology, and Issues, Ethics, and Legal Aspects related to technology.

The topics covered in their research include Online Learning and Analytics, Topic Modeling, Educational Games and Gamification, Innovative Teaching and Learning Methods, Nursing Diagnosis and Documentation, Artificial Intelligence in Healthcare and Education, and Machine Learning in Healthcare.

Tapio Salakoski has authored several papers in various academic venues. Recent publications include:

  • Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative, 2021, Journal of Advanced Nursing
  • Long Term Effects on Technology Enhanced Learning: The Use of Weekly Digital Lessons in Mathematics, 2020, Informatics in Education
  • Limits and Virtues of Educational Technology in Elementary School Mathematics, 2020, Journal of Educational Technology Systems
  • Neural Network and Random Forest Models in Protein Function Prediction, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • Assisting nurses in care documentation: from automated sentence classification to coherent document structures with subject headings, 2020, Journal of Biomedical Semantics

Frequent publication venues for Salakoski include Studies in Health Technology and Informatics, Natural Language Engineering, Journal of Advanced Nursing, Informatics in Education, and Journal of Educational Technology Systems.

The scientist often collaborates with other researchers, including Laura-Maria Peltonen, Sanna Salanterä, Mikko-Jussi Laakso, Hans Moen, and Filip Ginter.

Best Publications

  • A large-scale evaluation of computational protein function prediction

    Predrag Radivojac;Wyatt T Clark;Tal Ronnen Oron;Alexandra M Schnoes

  • BioInfer: a corpus for information extraction in the biomedical domain

    Sampo Pyysalo;Filip Ginter;Juho Heimonen;Jari Björne

  • Distributional Semantics Resources for Biomedical Text Processing

    S Pyysalo;F Ginter;H Moen;T Salakoski

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

  • The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

    Naihui Zhou;Yuxiang Jiang;Timothy R. Bergquist;Alexandra J. Lee

  • All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning

    Antti Airola;Sampo Pyysalo;Jari Björne;Tapio Pahikkala

  • Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative

    Charlene Esteban Ronquillo;Charlene Esteban Ronquillo;Laura Maria Peltonen;Lisiane Pruinelli;Charlene H. Chu

  • Comparative analysis of five protein-protein interaction corpora

    Sampo Pyysalo;Antti Airola;Juho Heimonen;Jari Björne

  • An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T Clark;Asma R Bankapur

  • Extracting Complex Biological Events with Rich Graph-Based Feature Sets

    Jari Björne;Juho Heimonen;Filip Ginter;Antti Airola

  • Multilingual is not enough: BERT for Finnish

    Antti Virtanen;Jenna Kanerva;Rami Ilo;Jouni Luoma

  • An experimental comparison of cross-validation techniques for estimating the area under the ROC curve

    Antti Airola;Tapio Pahikkala;Willem Waegeman;Bernard De Baets

  • Regularized Machine Learning in the Genetic Prediction of Complex Traits

    Sebastian Okser;Tapio Pahikkala;Antti Airola;Tapio Salakoski

  • Complex event extraction at PubMed scale

    Jari Björne;Filip Ginter;Sampo Pyysalo;Jun'ichi Tsujii

  • Why complicate things?: introducing programming in high school using Python

    Linda Grandell;Mia Peltomäki;Ralph-Johan Back;Tapio Salakoski

  • Generalizing Biomedical Event Extraction

    Jari Björne;Tapio Salakoski

  • Large-scale event extraction from literature with multi-level gene normalization

    Sofie van Landeghem;Jari Björne;Jari Björne;Chih Hsuan Wei;Kai Hakala

  • What about a simple language? Analyzing the difficulties in learning to program

    Linda Mannila;Mia Peltomäki;Tapio Salakoski

  • VILLE: a language-independent program visualization tool

    Teemu Rajala;Mikko-Jussi Laakso;Erkki Kaila;Tapio Salakoski

  • Building the essential resources for Finnish: the Turku Dependency Treebank

    Katri Haverinen;Jenna Nyblom;Timo Viljanen;Veronika Laippala

  • SELECTION OF A REPRESENTATIVE SET OF STRUCTURES FROM BROOKHAVEN PROTEIN DATA-BANK

    Jorma Boberg;Tapio Salakoski;Mauno Vihinen

  • Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy

    Yuxiang Jiang;Tal Ronnen Oron;Wyatt T. Clark;Asma R. Bankapur

Frequent Co-Authors

Filip Ginter
Filip Ginter University of Turku
Tapio Pahikkala
Tapio Pahikkala University of Turku
Sampo Pyysalo
Sampo Pyysalo University of Turku
Bernard De Baets
Bernard De Baets Ghent University
Hannu Tenhunen
Hannu Tenhunen Royal Institute of Technology
Christophe Dessimoz
Christophe Dessimoz University College London
Yves Van de Peer
Yves Van de Peer Ghent University
Mauno Vihinen
Mauno Vihinen Lund University
David T. Jones
David T. Jones University College London
Daisuke Kihara
Daisuke Kihara Purdue University West Lafayette

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