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
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
Frustrated opinion dynamics on real networks and its predictors
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
Weighted Temporal Event Graphs and Temporal-Network Connectivity
A simple model of edit activity in Wikipedia
Knowledge mining of unstructured information: application to cyber domain
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