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.


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

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

Frustrated opinion dynamics on real networks and its predictors

Daichi Kuroda, Kimmo Kaski, Takashi Shimada 2023 Frontiers in Physics

Segmentation stability of human head and neck cancer medical images for radiotherapy applications under de-identification conditions: Benchmarking data sharing and artificial intelligence use-cases

Jaakko Sahlsten, Kareem A. Wahid, Enrico Glerean, Joel Jaskari, Mohamed A. Naser, Renjie He, Benjamin H. Kann, Antti Mäkitie, Clifton D. Fuller, Kimmo Kaski 2023 FRONTIERS IN ONCOLOGY

Weighted Temporal Event Graphs and Temporal-Network Connectivity

Jari Saramäki, Arash Badie Modiri, Abbas K. Rizi, Mikko Kivelä, Marton Karsai 2023 Temporal Network Theory

A simple model of edit activity in Wikipedia

Takashi Shimada, Fumiko Ogushi, János Török, János Kertész, Kimmo Kaski 2023 Physica A: Statistical Mechanics and its Applications

Knowledge mining of unstructured information: application to cyber domain

Tuomas Takko, Kunal Bhattacharya, Martti Lehto, Pertti Jalasvirta, Aapo Cederberg, Kimmo Kaski 2023 Scientific Reports

Modelling exposure between populations using networks of mobility during COVID-19

Tuomas Takko, Kunal Bhattacharya, Kimmo Kaski 2023 Frontiers in Physics
More information on our research in the Aalto research portal.
Research portal
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