The Leeds Institute for Data Analytics is pleased to present the next seminar in our series showcasing data analytics.
The seminar will be held in 9.59, Worsley Building at 3.30pm on Thursday 7th March.
I will provide an overview of research topics I have worked over the years, with application in the healthcare domain. The key theme of my research is capitalizing on rich sources of data, and developing approaches to extract domain-specific information to develop clinical decision support tools and facilitate better-informed decisions. I will demonstrate how raw data such as voice, actigraphy, sleep, and geolocation can be used to monitor chronic diseases. My main focus will be on the design of new algorithmic data mining approaches and the development of decision support tools. I will touch upon applications including (1) using speech to remotely assess Parkinson’s disease symptom severity, (2) using passively collected data from wearables and smartphones to monitor mental disorders such as bipolar disorders, borderline personality disorders, and post-traumatic stress disorders.
Thanasis Tsanas is a Chancellor’s Fellow in Data Science at the Usher Institute of Population Health and Informatics, University of Edinburgh, where he leads the Data Analytics Research and Technology in Healthcare (DARTH) group, currently supervising 6 PhD students. He received the Andrew Goudie award (top PhD student across all disciplines, St. Cross College, University of Oxford, 2011), the EPSRC Doctoral Prize award (2012), the young scientist award (MAVEBA, 2013), and the EPSRC Statistics and Machine Learning award (2015), and was a key member of the team that won the annual Physionet competition on ‘Predicting mortality of ICU patients’ (2012). He sits on the Editorial Board of JMIR Mental Health, and is an Associate Editor for JMIR uHealth and mHealth. Thanasis helps lead the development of the NHS Digital Academy leadership programme via development of the ‘Decision Support and Actionable Data Analytics’ module.
Designing algorithms for counting steps in people with pathological gait using accelerometer data
Valeria Fillipou (PhD student, LIDA)
Methods for early diagnosis of Parkinson’s disease from videos
Dr Stefan Williams (Specialist Registrar in Neurology, University of Leeds)
Developing clinical decision support tools to monitor chronic diseases using biomedical signal processing and statistical machine learning
Networking reception with drinks and nibbles, hosted in LIDA’s staff kitchen, Level 11 Worsley building
Our seminars are free and open to all but places must be pre-booked.
To register to attend this seminar please email Hayley Irving with your name, position, and organisation/faculty.