Department of Computer Science

Digital Health and Wellbeing

The goal of our research group is to have a positive impact on healthcare and societal wellbeing through research and applying data-driven methods. Our approach includes international and multidisciplinary collaborations with a diverse set of researchers and domain experts from universities, hospitals, and industry. Under the leadership of Prof. Kimmo Kaski, our diverse team is dedicated to the advancement of healthcare, social networks, and their socio-economic impacts.
digital-health

Research

Data Science & Artificial Intelligence for Healthcare

Our Data Science and AI for healthcare research includes a range of topics from automatic medical image analysis, such as diabetic retinopathy severity grading and pathological tissue segmentation. Our research methods include deep learning neural networks and statistical Bayesian approaches. In order to improve the trustworthiness of deep learning approaches, we aim to develop their explainability with techniques such as uncertainty quantification and adding human-in-the-loop components through interactivity.

Techno-Social Networks & Socio-Economic Modeling 

We provide essential insights into the socio-economic effects of pandemics and the dynamics of social networks through sophisticated data analytics, machine learning, and computational modelling. Our research into residential clustering and the mobility of ethnic minorities in Finland reveals how urban migrational patterns and social factors contribute to spatial distributions and community dynamics. This comprehensive approach aids the policymakers and public alike, offering new perspectives on managing societal challenges and promoting wellbeing.

Interested in joining us?

We are looking for Doctoral students and Postdoctoral researchers in Data Science & AI for Healthcare. Contact [email protected]

Latest publications

Organizational changes and research performance : A multidimensional assessment

José Luis Jiménez-Andrade, RIcardo Arencibia-Jorge, Miguel Robles-Pérez, Julia Tagüeña, Tzipe Govezensky, Humberto Carrillo-Calvet, Rafael A. Barrio, Kimmo Kaski 2024 Research Evaluation

COVID-19 Twitter discussions in social media : Disinformation, topical complexity, and health impacts

Mikhail Oet, Xiaomu Zhou, Kuiming Zhao, Tuomas Takko 2024 Handbook of Social Computing

Application of simultaneous uncertainty quantification and segmentation for oropharyngeal cancer use-case with Bayesian deep learning

Jaakko Sahlsten, Joel Jaskari, Kareem A. Wahid, Sara Ahmed, Enrico Glerean, Renjie He, Benjamin H. Kann, Antti Mäkitie, Clifton D. Fuller, Mohamed A. Naser, Kimmo Kaski 2024 Communications Medicine

Deep learning for 3D cephalometric landmarking with heterogeneous multi-center CBCT dataset

Jaakko Sahlsten, Jorma Järnstedt, Joel Jaskari, Hanna Naukkarinen, Phattaranant Mahasantipiya, Arnon Charuakkra, Krista Vasankari, Ari Hietanen, Osku Sundqvist, Antti Lehtinen, Kimmo Kaski 2024 PloS one

A modelling study to explore the effects of regional socio-economics on the spreading of epidemics

Jan E. Snellman, Rafael A. Barrio, Kimmo K. Kaski, Maarit J. Korpi–Lagg 2024 Journal of Computational Social Science

Socio-economic pandemic modelling : case of Spain

Jan E. Snellman, Nadia L. Barreiro, Rafael A. Barrio, Cecilia I. Ventura, Tzipe Govezensky, Kimmo K. Kaski, Maarit J. Korpi-Lagg 2024 Scientific Reports

Harnessing uncertainty in radiotherapy auto-segmentation quality assurance

Kareem A. Wahid, Jaakko Sahlsten, Joel Jaskari, Michael J. Dohopolski, Kimmo Kaski, Renjie He, Enrico Glerean, Benjamin H. Kann, Antti Mäkitie, Clifton D. Fuller, Mohamed A. Naser, David Fuentes 2024 Physics and Imaging in Radiation Oncology

Impact of institutional organization on research productivity and multidisciplinarity

Alberto García-Rodríguez, R. A. Barrio, Tzipe Govezensky, Julia Tagüeña, Miguel Robles Pérez, Humberto Carrillo Calvet, José Luis Jiménez Andrade, Ricardo Arencibia-Jorge, Kimmo Kaski 2023 Frontiers in Physics

Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset

Jorma Järnstedt, Jaakko Sahlsten, Joel Jaskari, Kimmo Kaski, Helena Mehtonen, Ari Hietanen, Osku Sundqvist, Vesa Varjonen, Vesa Mattila, Sangsom Prapayasatok, Sakarat Nalampang 2023 Scientific Reports
More information on our research in the Aalto research portal.
Research portal

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