Earlier this month the University of Nottingham published a study in PloSOne about a new artificial intelligence model that uses machine learning to predict the risk of premature death, using banked health data (on age and lifestyle factors) from Brits aged 40 to 69.

This study comes months after a joint study between UC San Francisco, Stanford, and Google, which reported results of machine-learning-based data mining of electronic health records to assess the likelihood that a patient would die in hospital.

One goal of both studies was to assess how this information might help clinicians decide which patients might most benefit from intervention.

As the conversation around artificial intelligence and medicine progresses, it is clear we must have specific oversight around the role of AI in determining and predicting death.

And even though researchers are talking about the problem, issues remain.

Case in point: The launch of a new Stanford institute for AI a few weeks ago came under scrutiny for its lack of ethnic diversity.

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