Can artificial intelligence detect hidden heart attacks?

Suitable for 14-19-year olds (secondary and high schools, and college), this article and accompanying activity sheet can be used in the classroom, STEM clubs and at home.

This resource links to KS4 and KS5 biology, computer science and engineering.

It can also be used as a careers resource and links to Gatsby Benchmarks:
Gatsby Benchmark 2: Learning from career and labour market information
Gatsby Benchmark 4: Linking curriculum learning to careers

• This teaching resource explains the work of Dr Salah Al-Zaiti (a nurse scientist at the University of Pittsburgh), Dr Christian Martin-Gill (an emergency physician at the University of Pittsburgh) and Dr Ervin Sejdić (a biomedical engineer at the University of Toronto). They have developed an AI tool that can diagnose a heart attack from a patient’s electrocardiogram (ECG).

• This resource also contains interviews with Salah, Christian and Ervin and offers an insight into careers in machine learning in medicine. If your students have questions for Salah, Christian and Ervin, they can send them to them online. All they need to do is to go to the article online (see the Futurum link below), scroll down to the end and type in the question(s). Salah, Christian and Ervin will reply!

• The activity sheet provides ‘talking points’ (based on Bloom’s Taxonomy) to prompt students to reflect on the team’s research and challenges them to design a new AI tool to detect a medical condition.

This resource was first published on Futurum Careers, a free online resource and magazine aimed at encouraging 14-19-year-olds worldwide to pursue careers in science, tech, engineering, maths, medicine (STEM) and social sciences, humanities and the arts for people and the economy (SHAPE).

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