Zobrazeno 1 - 10
of 325
pro vyhledávání: '"Barnaghi P."'
Large language models (LLMs), trained on diverse data effectively acquire a breadth of information across various domains. However, their computational complexity, cost, and lack of transparency hinder their direct application for specialised tasks.
Externí odkaz:
http://arxiv.org/abs/2411.17284
In Explainable AI, rule extraction translates model knowledge into logical rules, such as IF-THEN statements, crucial for understanding patterns learned by black-box models. This could significantly aid in fields like disease diagnosis, disease progr
Externí odkaz:
http://arxiv.org/abs/2406.17885
Publikováno v:
International Conference on Learning Representations 2024 Workshop on Learning from Time Series For Health
Time-series representation learning is a key area of research for remote healthcare monitoring applications. In this work, we focus on a dataset of recordings of in-home activity from people living with Dementia. We design a representation learning m
Externí odkaz:
http://arxiv.org/abs/2405.04494
Microcontroller Units (MCUs) are ideal platforms for edge applications due to their low cost and energy consumption, and are widely used in various applications, including personalized machine learning tasks, where customized models can enhance the t
Externí odkaz:
http://arxiv.org/abs/2403.08040
Autor:
Fletcher-Lloyd, Nan, Serban, Alina-Irina, Kolanko, Magdalena, Wingfield, David, Wilson, Danielle, Nilforooshan, Ramin, Barnaghi, Payam, Soreq, Eyal
Malnutrition and dehydration are strongly associated with increased cognitive and functional decline in people living with dementia (PLWD), as well as an increased rate of hospitalisations in comparison to their healthy counterparts. Extreme changes
Externí odkaz:
http://arxiv.org/abs/2307.11126
Publikováno v:
Communications Medicine, Vol 4, Iss 1, Pp 1-10 (2024)
Abstract Background Nocturnal disturbances are a common symptom experienced by People Living with Dementia (PLWD), and these often present prior to diagnosis. Whilst sleep anomalies have been frequently reported, most studies have been conducted in l
Externí odkaz:
https://doaj.org/article/be9fbdf6c7d446feae2a45b9f6dcafa6
Autor:
Megan E. Parkinson, Rebecca M. Smith, Karen Tanious, Francesca Curtis, Rebecca Doherty, Lorena Colon, Lucero Chena, Sophie C. Horrocks, Matthew Harrison, Michael B. Fertleman, Melanie Dani, Payam Barnaghi, David J. Sharp, the UK Dementia Research Institute Care Research & Technology Research Group, Lucia M. Li
Publikováno v:
BMC Geriatrics, Vol 24, Iss 1, Pp 1-16 (2024)
Abstract Background Home monitoring systems utilising artificial intelligence hold promise for digitally enhanced healthcare in older adults. Their real-world use will depend on acceptability to the end user i.e. older adults and caregivers. We explo
Externí odkaz:
https://doaj.org/article/20aaeaca983648a98824b77b3ec8285a
Autor:
Huang, Yushan, Zhao, Yuchen, Capstick, Alexander, Palermo, Francesca, Haddadi, Hamed, Barnaghi, Payam
Current methods for pattern analysis in time series mainly rely on statistical features or probabilistic learning and inference methods to identify patterns and trends in the data. Such methods do not generalize well when applied to multivariate, mul
Externí odkaz:
http://arxiv.org/abs/2302.11654
When data is generated by multiple sources, conventional training methods update models assuming equal reliability for each source and do not consider their individual data quality. However, in many applications, sources have varied levels of reliabi
Externí odkaz:
http://arxiv.org/abs/2212.02895
In this work, we apply information theory inspired methods to quantify changes in daily activity patterns. We use in-home movement monitoring data and show how they can help indicate the occurrence of healthcare-related events. Three different types
Externí odkaz:
http://arxiv.org/abs/2210.01736