Supportive Cancer Care

An AI-powered chatbot to help cancer patients find and access supportive care services such as counselling, social work, and rehabilitation, at the right time in their care journey.

Adapting an chatbot to support exercise professionals in providing personalized, evidence-based behaviour change support for people with colon cancer.

Developing network-based models and Python visualization tools to map supportive cancer care referral pathways and identify missed opportunities or delays in accessing mental health services.

Using machine learning to explore whether personalized cancer treatment approaches work equally well for all patients, regardless of their background.

Examining what is known about how cancer patients and clinicians perceive, want, and respond to artificial intelligence in their care, to ensure the tools we build reflect what people actually need.

Using NLP applied to clinical notes to identify cancer patients who would benefit from psychiatric referral but may not yet have been flagged.

An AI tool to help clinical teams assess incoming referrals, identify gaps in information, and route patients to the most appropriate services more efficiently.

Surveying and interviewing patients to understand their comfort with and concerns about artificial intelligence being used in their care.

A qualitative research study exploring how patients experience the process of being referred to supportive care services, and how they feel about the idea of AI being involved in that process.

Examining how social isolation and psychological distress relate to outcomes for cancer patients, to better understand the human factors that influence survival.