DARTH group mission
Ever-increasing healthcare provision demands strain national health systems globally, which struggle to meet patients' needs. There is a growing unmet clinical need to develop accurate, robust, practical decision support tools to facilitate diagnosis, assessment, and symptom monitoring to improve patient health and care.
We are a dynamic research group based at the Usher Institute, Edinburgh Medical School, University of Edinburgh working at the interface of engineering, mathematics, informatics, and medicine. We passionately believe we can design and provide effective solutions which will revolutionize contemporary healthcare delivery through capitalizing technology and harnessing data.
We develop and apply signal processing and statistical machine learning algorithms to explore data and decipher complicated concealed statistical relationships. Our algorithms are directly driven by and validated on complicated real-world problems, aiming to facilitate interpretation of the underlying key mechanisms of the modelled system. Our work is inherently multi-disciplinary and we collaborate with industrial partners and researchers worldwide. We tackle challenging problems in healthcare domains from neurodegenerative disorders and mental health, to asthma, cardiovascular disease, and neonatal monitoring.
New book edited by Thanasis summarizing the state-of-art developments in Pervasive Computing as part of the International Conference in Pervasive Computing Technologies for Healthcare where he served as General Chair. This is free to download directly from the publisher for the first four weeks!
26 Oct 2023
10 Aug 2023
23 Jul 2023
21 Jun 2023
1 Jun 2023
26 Apr 2023
19 Apr 2023
10 Jan 2023
Journal paper accepted in ACM Transactions on Computing for Healthcare! The study proposes a framework to tackle challenges with limited sample sizes invoking transfer learning and deep learning, applied in mental well-being assessment.
Journal paper accepted in Cell Reports Medicine! The study discusses the use of digital technologies to facilitate symptom tracking and management in endometriosis.
Journal paper accepted in Information Fusion! The study provides an overview of key advances in applied AI summarizing building on the momentum and inter-disciplinary collaborations in IWINAC22'.
New book published by Springer where Thanasis is Lead Editor, summarizing the state of the art in Pervasive Computing in Healthcare, following the organization of the 2022 conference (Thessaloniki, Greece, 12/2022).
Holly Tibble, who had completed her PhD and post-doc with the DARTH group starts on a prestigious Chancellor's Fellowship! Holly will be affiliated with DARTH and progressively setting her own independent research group.
Journal paper accepted in BMC Medical Research Methodology! We provide a framework to infer medication adherence from large-scale electronic health records using asthma as a testbed.
Journal paper accepted in JAMA Network Open! We demonstrate that birth gestational age and socioeconomic status are associated with early brain development in neonates.
Journal paper accepted in Sensors! We demonstrate, for the first time, that mining longitudinal continuous temperature data collected from a smartwatch can provide clinically useful information, using stroke as a testbed.