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02/09/2023
Lightweight Transformers for Clinical Natural Language Processing
Specialised pre-trained language models are becoming more frequent in NL...
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11/29/2022
G-CMP: Graph-enhanced Contextual Matrix Profile for unsupervised anomaly detection in sensor-based remote health monitoring
Sensor-based remote health monitoring is used in industrial, urban and h...
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10/12/2022
MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers
Pre-trained Language Models (LMs) have become an integral part of Natura...
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09/07/2022
On the Effectiveness of Compact Biomedical Transformers
Language models pre-trained on biomedical corpora, such as BioBERT, have...
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01/09/2022
Privacy-aware Early Detection of COVID-19 through Adversarial Training
Early detection of COVID-19 is an ongoing area of research that can help...
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10/19/2021
Designing A Clinically Applicable Deep Recurrent Model to Identify Neuropsychiatric Symptoms in People Living with Dementia Using In-Home Monitoring Data
Agitation is one of the neuropsychiatric symptoms with high prevalence i...
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03/03/2021
A Hamiltonian Monte Carlo Model for Imputation and Augmentation of Healthcare Data
Missing values exist in nearly all clinical studies because data for a v...
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02/27/2019
Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressions
We introduce a new method to tag Multiword Expressions (MWEs) using a li...
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08/30/2016
