Developing an AI-decision support tool for ED visits in oncology to augment compassion-centered care

Clinician Scientist, Sunnybrook Research Institute Many cancer patients access the emergency department (ED). However, 60% of ED visits are preventable with limited tools to stratify risk groups and personalize care plans. Ultimately, this would avoid anxiety and distress. Here, William proposes to develop an artificial intelligence (AI)-guided decision support tool to improve management and follow-up…

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Recognizing warnings in adults at risk of life-threatening diagnoses using AI

Researcher, Unity Health Toronto & Clinician Scientist, Sinai Health Delays, and often omissions, of life-threatening diagnoses are common, especially with hospitalized patients. To render the correct diagnosis, healthcare providers need sufficient uninterrupted time to review a patient’s medical record and speak with the patient directly, but the chaotic inpatient environment presents many challenges: interruptions, task-switching,…

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Identifying patient‐validated compassion and equity concepts in community care clinical notes through natural language processing

Assistant Professor, The University of British Columbia – Okanagan In Charlene’s project, she aims to develop and test compassion and equity-grounded natural language processing (NLP) application to leverage otherwise unused community nursing clinical notes. She will develop a dictionary that merges understandings of equity and compassionate care from the perspectives of community nurses and patients…

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