34 citations · 52 across the 11 of their papers we have counts for
11 papers
Interpreting Differentiable Latent States for Healthcare Time-series Data
Yu Chen, Nivedita Bijlani, Samaneh Kouchaki +1
Machine learning enables extracting clinical insights from large temporal datasets. The applications of such machine learning models include identifying disease patterns and predic…
Lightweight Transformers for Clinical Natural Language Processing
Omid Rohanian, Mohammadmahdi Nouriborji, Hannah Jauncey +5
Specialised pre-trained language models are becoming more frequent in NLP since they can potentially outperform models trained on generic texts. BioBERT and BioClinicalBERT are two…
G-CMP: Graph-enhanced Contextual Matrix Profile for unsupervised anomaly detection in sensor-based remote health monitoring
Nivedita Bijlani, Oscar Mendez Maldonado, Samaneh Kouchaki
Sensor-based remote health monitoring is used in industrial, urban and healthcare settings to monitor ongoing operation of equipment and human health. An important aim is to interv…
MiniALBERT: Model Distillation via Parameter-Efficient Recursive Transformers
Mohammadmahdi Nouriborji, Omid Rohanian, Samaneh Kouchaki +1
Pre-trained Language Models (LMs) have become an integral part of Natural Language Processing (NLP) in recent years, due to their superior performance in downstream applications. I…
On the Effectiveness of Compact Biomedical Transformers
Omid Rohanian, Mohammadmahdi Nouriborji, Samaneh Kouchaki +1
Language models pre-trained on biomedical corpora, such as BioBERT, have recently shown promising results on downstream biomedical tasks. Many existing pre-trained models, on the o…
Privacy-aware Early Detection of COVID-19 through Adversarial Training
Omid Rohanian, Samaneh Kouchaki, Andrew Soltan +4
Early detection of COVID-19 is an ongoing area of research that can help with triage, monitoring and general health assessment of potential patients and may reduce operational stra…
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 +6
Agitation is one of the neuropsychiatric symptoms with high prevalence in dementia which can negatively impact the Activities of Daily Living (ADL) and the independence of individu…
Semi-supervised Learning for Identifying the Likelihood of Agitation in People with Dementia
Roonak Rezvani, Samaneh Kouchaki, Ramin Nilforooshan +2
Interpreting the environmental, behavioural and psychological data from in-home sensory observations and measurements can provide valuable insights into the health and well-being o…
A Hamiltonian Monte Carlo Model for Imputation and Augmentation of Healthcare Data
Narges Pourshahrokhi, Samaneh Kouchaki, Kord M. Kober +2
Missing values exist in nearly all clinical studies because data for a variable or question are not collected or not available. Inadequate handling of missing values can lead to bi…
Bridging the Gap: Attending to Discontinuity in Identification of Multiword Expressions
Omid Rohanian, Shiva Taslimipoor, Samaneh Kouchaki +2
We introduce a new method to tag Multiword Expressions (MWEs) using a linguistically interpretable language-independent deep learning architecture. We specifically target discontin…
Visualisation of Survey Responses using Self-Organising Maps: A Case Study on Diabetes Self-care Factors
Santosh Tirunagari, Simon Bull, Samaneh Kouchaki +2
Due to the chronic nature of diabetes, patient self-care factors play an important role in any treatment plan. In order to understand the behaviour of patients in response to medic…