Alexander Capstick

According to our database, Alexander Capstick authored at least 12 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Two-Stage Representation Learning for Analyzing Movement Behavior Dynamics in People Living with Dementia.

Jin Cui, Alexander Capstick, Payam M. Barnaghi, Gregory Scott

CoRR, February, 2025

Evaluating Spoken Language as a Biomarker for Automated Screening of Cognitive Impairment.

Maria R. Lima, Alexander Capstick, Fatemeh Geranmayeh, Ramin Nilforooshan, Maja Mataric, Ravi Vaidyanathan, Payam M. Barnaghi

CoRR, January, 2025

2024

Digital remote monitoring for screening and early detection of urinary tract infections.

Alexander Capstick, Francesca Palermo, Kimberley Zakka, Nan Fletcher-Lloyd, Chloe Walsh, Tianyu Cui, Samaneh Kouchaki, Raphaella Jackson, Martin Tran, Michael Crone, Kirsten Jensen, Paul S. Freemont, Ravi Vaidyanathan, Magdalena Kolanko, Jessica True, Sarah Daniels, David Wingfield, Ramin Nilforooshan, Payam M. Barnaghi

npj Digit. Medicine, 2024

Using Large Language Models for Expert Prior Elicitation in Predictive Modelling.

Alexander Capstick, Rahul G. Krishnan, Payam M. Barnaghi

CoRR, 2024

Enabling Regional Explainability by Automatic and Model-agnostic Rule Extraction.

Yu Chen, Tianyu Cui, Alexander Capstick, Nan Fletcher-Lloyd, Payam M. Barnaghi

CoRR, 2024

Representation Learning of Daily Movement Data Using Text Encoders.

Alexander Capstick, Tianyu Cui, Yu Chen, Payam M. Barnaghi

CoRR, 2024

Analyzing entropy features in time-series data for pattern recognition in neurological conditions.

Yushan Huang, Yuchen Zhao, Alexander Capstick, Francesca Palermo, Hamed Haddadi, Payam M. Barnaghi

Artif. Intell. Medicine, 2024

Urinary Tract Infection Detection in Digital Remote Monitoring: Strategies for Managing Participant-Specific Prediction Complexity.

Kexin Fan, Alexander Capstick, Ramin Nilforooshan, Payam M. Barnaghi

Proceedings of the IEEE International Conference on E-health Networking, 2024

2023

Information Theory Inspired Pattern Analysis for Time-series Data.

Yushan Huang, Yuchen Zhao, Alexander Capstick, Francesca Palermo, Hamed Haddadi, Payam M. Barnaghi

CoRR, 2023

Predicting Targets with Data from Non-Conforming Sources.

Alexander Capstick, Payam M. Barnaghi

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

2022

Loss Adapted Plasticity in Deep Neural Networks to Learn from Data with Unreliable Sources.

Alexander Capstick, Francesca Palermo, Payam M. Barnaghi

CoRR, 2022

2021

Designing A Clinically Applicable Deep Recurrent Model to Identify Neuropsychiatric Symptoms in People Living with Dementia Using In-Home Monitoring Data.

Francesca Palermo, Honglin Li, Alexander Capstick, Nan Fletcher-Lloyd, Yuchen Zhao, Samaneh Kouchaki, Ramin Nilforooshan, David J. Sharp, Payam M. Barnaghi

CoRR, 2021