Digital Health and Wellbeing
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
COVID-19 Twitter discussions in social media : Disinformation, topical complexity, and health impacts
Presidential communications on Twitter during the COVID-19 pandemic : Mediating polarization and trust, moderating mobility
Application of simultaneous uncertainty quantification and segmentation for oropharyngeal cancer use-case with Bayesian deep learning
Deep learning for 3D cephalometric landmarking with heterogeneous multi-center CBCT dataset
A modelling study to explore the effects of regional socio-economics on the spreading of epidemics
Socio-economic pandemic modelling : case of Spain
Harnessing uncertainty in radiotherapy auto-segmentation quality assurance
Impact of institutional organization on research productivity and multidisciplinarity
Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset
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