Predicting Risk of Aggressive Responsive Behaviours among People Suffering from Dementia using Natural Language Processing (NLP) and Machine Learning (ML).

Patients with dementia will eventually experience significant loss of cognitive function. Many will have difficulty properly communicating life’s challenges and instead become agitated, resulting in verbal or physical aggression. Monitoring the risk of a resident harming themselves or others due to aggressive behavior is a priority within a long-term care facility where dementia is present. Caregivers at Shannex regularly record resident health and behaviour using computing systems. Each of these systems digitally record information either as structured data or unstructured text, providing an on-going log of each resident’s patient history. The objective of this project is to use natural language processing (NLP) and machine learning (ML) techniques to develop models that can predict the probability of a resident exhibiting aggressive behaviours that may harm themselves or others within the next week.

Faculty Supervisor:

Daniel Silver


Maryam Tajeddin




Computer science


Health care and social assistance




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