Antti Airola profile picture
Antti
Airola
Assistant Professor, Health Technology
D.Sc. (Tech.)

Contact

+358 29 450 4193
+358 50 517 8711
Vesilinnantie 5
20500
Turku

Areas of expertise

artificial intelligence
data analytics
machine learning
health technology

Biography

Antti Airola, is an Assistant Professor (tenure track) of data science in the area of Health Technology at the University of Turku. He has co-authored over 80 peer-reviewed articles, won multiple international data science competitions, and received several research excellence awards such as the the HATUTUS award for the best PhD thesis in the area of pattern recognition in Finland (2010 - 2011) and IEEE Computational Intelligence Society Outstanding Transactions on Fuzzy Systems Paper award (2015). He is currently working as responsible leader in several Academy of Finland and Business Finland funded research projects.

Teaching

Airola's main research areas are in the area of machine learning and data science, especially their applications in the health domain. He currently leads two Academy of Finland funded projects related to the area of biomedical interaction prediction, and the Business Finland PRIVASA project on privacy-preserving AI for health data.

Research

Airola is currently responsible for teaching the course TKO_3103 Data Analysis and Knowledge Discovery, as well as thesis supervision work (BSc, MSc, PhD). He has developed materials for and taught in many courses in the area of data and computer science, is responsible for developing the curriculum for both national BSc and MSc Medical and health technology programmes, as well as the international MSc programme in Health technology, and directs the AI Academy that coordinates AI related teaching between the faculties.

Publications

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Robust ECG R-peak detection using LSTM (2020)

ACM Symposium on Applied Computing
Laitala J., Jiang M., Syrjälä E., Naeini E.K., Airola A., Rahmani A.M., Dutt N.D., Liljeberg P.
(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))

Prostate Cancer Risk Stratification in Men With a Clinical Suspicion of Prostate Cancer Using a Unique Biparametric MRI and Expression of 11 Genes in Apparently Benign Tissue: Evaluation Using Machine-Learning Techniques (2020)

Journal of Magnetic Resonance Imaging
Ileana Montoya Perez, Ivan Jambor, Tapio Pahikkala, Antti Airola, Harri Merisaari, Jani Saunavaara, Saeid Alinezhad, Riina-Minna Väänänen, Terhi Tallgrén, Janne Verho, Aida Kiviniemi, Otto Ettala, Juha Knaapila, Kari T. Syvänen, Markku Kallajoki, Paula Vainio, Hannu J. Aronen, Kim Pettersson, Peter J. Boström, Pekka Taimen
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))