Successfully organized the 16th International Conference on Pervasive Computing Technologies in Healthcare, where Thanasis served as the Main Conference Chair.

Journal paper accepted in the International Journal of Medical Informatics! The study defines clinical subtypes of asthma using electronic health records and demonstrates generalizability of findings in two large databases (SAIL, OPCRD).

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Thanasis has been promoted to Full Professor at the Usher Institute, Edinburgh Medical School. The formal title is Personal Chair of Digital Health and Data Science.

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Journal paper accepted in BMC Pulmonary Medicine! This study mined electronic prescription records from over 670,000 people and 41m prescriptions to estimate asthma symptom trajectories towards informing asthma management.

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Journal paper accepted in Computers in Biology and Medicine! This study develops an intelligent and lightweight system mining electromyography sensor data, thus automatically monitoring eating behaviour and providing real-time feedback.

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Journal paper accepted in Sensors! The study builds a robust framework to analyze three dimensional acceleration data proposing a new robust acceleration summary measure. Check the accompanying MATLAB source code.

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Alan Turing blogpost highlighting our recent work on feature selection that has been published in Patterns! The post makes an argument for developing robust and versatile algorithms. Check it out here.

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Journal paper accepted and published jointly in BMJ and Nature Medicine! This is on reporting guidelines for clinical decision support systems, which we call DECIDE-AI.

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Journal paper accepted in BMJ! The study includes a systematic review, pooling together data from 14 studies for meta analysis and the development of a decision support tool to assess the probability of acute heart failure.

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Conference paper accepted in IEEE EMBC! This study focuses on estimating medication adherence from large electronic health records using asthma as a testbed.

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Journal paper accepted in Springer Nature Computer Science! This study focuses on using speech to objectively identify Parkinson's subtypes. Results are generalizable across three countries, including external validation.

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Two conference papers accepted at IWINAC! Both papers provide new mechanistic insights into Parkinson's through advanced processing of speech signals.

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Journal paper accepted in Patterns - also check the accompanying source code! This study introduces a new robust feature selection algorithm and tests side-by-side performance of 20 feature selection algorithms across 12 datasets.

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Journal paper accepted in Lancet Digital Health! This study validates the use of our previously published algorithm to inform myocardial infarction diagnosis in a large non-controlled population.