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 )

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 )

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 )

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 )

Benchmarking Evaluation Protocols for Classifiers Trained on Differentially Private Synthetic Data (2024)

IEEE Access

Movahedi, Parisa; Nieminen, Valtteri; Perez, Ileana Montoya; Daafane, Hiba; Sukhwal, Dishant; Pahikkala, Tapio; Airola, Antti

(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )

Predicting pairwise interaction affinities with ℓ0-penalized least squares-a nonsmooth bi-objective optimization based approach∗ (2024)

Optimization Methods and Software

Paasivirta Pauliina, Numminen Riikka, Airola Antti, Karmitsa Napsu, Pahikkala Tapio

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

Tapio

Pahikkala

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

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)

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)

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

Benchmarking Evaluation Protocols for Classifiers Trained on Differentially Private Synthetic Data (2024)

Predicting pairwise interaction affinities with ℓ0-penalized least squares-a nonsmooth bi-objective optimization based approach∗ (2024)