Tapio Pahikkala

Securing deep learning models with differential privacy for cardiovascular disease prediction (2026)

Biomedical Signal Processing and Control

Orabe, Zoher; Vasankari, Antti; Pahikkala, Tapio; Kaisti, Matti; Airola, Antti

(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

Hospital Participation in Federated Learning: Evaluating Sustainability and Clinical Utility (2025)

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Kazlouski, Andrei; Montoya Perez, Ileana; Pahikkala, Tapio; Airola, Antti

(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)

Towards practical federated learning and evaluation for medical prediction models (2025)

International Journal of Medical Informatics

Kazlouski, Andrei; Montoya, Perez Ileana; Noor, Faiza; Högerman, Mikael; Ettala, Otto; Pahikkala, Tapio; Airola, Antti

(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

Limited memory bundle DC algorithm for sparse pairwise kernel learning (2025)

Journal of Global Optimization

Karmitsa, Napsu; Joki, Kaisa; Airola, Antti; Pahikkala, Tapio

(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

Stochastic limited memory bundle algorithm for clustering in big data (2025)

Pattern Recognition

Karmitsa, Napsu; Eronen, Ville-Pekka; Mäkelä, Marko M.; Pahikkala, Tapio; Airola, Antti

(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

Improved diagnostic performance of a phage display antibody-assisted intact free PSA assay as used in the four kallikrein concept applied to the IMPROD/multi-IMPROD study (2025)

Clinica Chimica Acta

Khan, Md. Ferdhos L.; Perez, Ileana M.; Kekki, Henna; Taimen, Pekka; Boström, Peter J.; Jambor, Ivan; Ettala, Otto; Pahikkala, Tapio; Pettersson, Kim

(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

Response to Commentary by Dehaene et al. on Synthetic Discovery is not only a Problem of Differentially Private Synthetic Data (2025)

Methods of Information in Medicine

Montoya Perez, Ileana; Movahedi, Parisa; Nieminen, Valtteri; Airola, Antti; Pahikkala, Tapio

(B1 Vertaisarvioimaton kirjoitus tieteellisessä lehdessä )

Does Differentially Private Synthetic Data Lead to Synthetic Discoveries? (2024)

Methods of Information in Medicine

Montoya Perez, Ileana; Movahedi, Parisa; Nieminen, Valtteri; Airola, Antti; Pahikkala, Tapio

(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

A comparison of embedding aggregation strategies in drug-target interaction prediction (2024)

BMC Bioinformatics

Iliadis Dimitrios, De Baets Bernard, Pahikkala Tapio, Waegeman Willem

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Finnish perspective on using synthetic health data to protect privacy: the PRIVASA project (2024)

Applied Computing and Intelligence

Pitkämäki, Tinja; Pahikkala, Tapio; Montoya Perez, Ileana; Movahedi, Parisa; Nieminen, Valtteri; Southerington, Tom; Vaiste, Juho; Jafaritadi, Mojtaba; Khan, Muhammad Irfan; Kontio, Elina; Ranttila, Pertti; Pajula, Juha; Pölönen, Harri; Degerli, Aysen; Plomp, Johan; Airola, Antti

(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

Tapio

Pahikkala

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Securing deep learning models with differential privacy for cardiovascular disease prediction (2026)

Hospital Participation in Federated Learning: Evaluating Sustainability and Clinical Utility (2025)

Towards practical federated learning and evaluation for medical prediction models (2025)

Limited memory bundle DC algorithm for sparse pairwise kernel learning (2025)

Stochastic limited memory bundle algorithm for clustering in big data (2025)

Improved diagnostic performance of a phage display antibody-assisted intact free PSA assay as used in the four kallikrein concept applied to the IMPROD/multi-IMPROD study (2025)

Response to Commentary by Dehaene et al. on Synthetic Discovery is not only a Problem of Differentially Private Synthetic Data (2025)

Does Differentially Private Synthetic Data Lead to Synthetic Discoveries? (2024)

A comparison of embedding aggregation strategies in drug-target interaction prediction (2024)

Finnish perspective on using synthetic health data to protect privacy: the PRIVASA project (2024)