Tapio Pahikkala
Professor
aatapa@utu.fi +358 29 450 4323 +358 50 345 5824 Office: 456D ORCID identifier: https://orcid.org/0000-0003-4183-2455 |
Machine learning, Data science, Artificial intelligence
Machine learning, Data science, Artificial intelligence
Tapio Pahikkala is a professor of computer science in the University of Turku, Finland, from which he also received his doctoral degree in 2008. He has authored more than 150 peer-reviewed scientific articles and participated in the winning teams of several international scientific competitions/challenges. He has led many research projects, supervised more than ten doctoral theses, held several positions of trust in academia and served in the program committees of numerous international conferences. His current research interests include theory and algorithmics of machine learning, data analysis, and artificial intelligence, as well as their applications on various different fields.
Theory and algorithmics of machine learning, data science and artificial intelligence as well as their practical applications in various different fields. Estimation of prediction performance with resampling methods, theory of resampling and cross-validation.
TKO_7092 Evaluation of Machine Learning Methods
- Prediction of biochemical recurrence in prostate cancer patients who underwent prostatectomy using routine clinical prostate multiparametric MRI and decipher genomic score (2019)
- Journal of Magnetic Resonance Imaging
(A1 Refereed original research article in a scientific journal) - Qualitative and Quantitative Reporting of a Unique Biparametric MRI: Towards Biparametric MRI-Based Nomograms for Prediction of Prostate Biopsy Outcome in Men With a Clinical Suspicion of Prostate Cancer (IMPROD and MULTI-IMPROD Trials) (2019)
- Journal of Magnetic Resonance Imaging
(A1 Refereed original research article in a scientific journal) - Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization (2019)
- PLoS ONE
(A1 Refereed original research article in a scientific journal) - Skin Conductance Response to Gradual-Increasing Experimental Pain (2019)
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society
(A4 Refereed article in a conference publication ) - The spatial leave-pair-out cross-validation method for reliable AUC estimation of spatial classifiers (2019)
- Data Mining and Knowledge Discovery
(A1 Refereed original research article in a scientific journal) - Tournament leave-pair-out cross-validation for receiver operating characteristic analysis (2019)
- Statistical Methods in Medical Research
(A1 Refereed original research article in a scientific journal) - A comparative study of pairwise learning methods based on Kernel ridge regression (2018)
- Neural Computation
(A1 Refereed original research article in a scientific journal) - Combined transcriptomics, proteomics and metabolomics analysis identifies metabolic pathways associated with the loss of cardiac regeneration (2018)
- Cardiovascular Research
(Other publication) - Comparison of estimators and feature selection procedures in forest inventory based on airborne laser scanning and digital aerial imagery (2018)
- Scandinavian Journal of Forest Research
(A1 Refereed original research article in a scientific journal) - Effect of homogenised and pasteurised versus native cows' milk on gastrointestinal symptoms, intestinal pressure and postprandial lipid metabolism (2018)
- International Dairy Journal
(A1 Refereed original research article in a scientific journal)



