AI to predict premature death accurately

As, technology is emerging, Artificial Intelligence AI was tasked to predict if individuals were at risk of premature death from chronic disease.

AI to predict premature death accuratelyExperts from University of Nottingham recently trained an AI system to evaluate a decade of general health data submitted by over half a million people in the UK.

The predictions of early death made by the AI algorithm were ‘significantly more accurate’ than the predictions delivered by a model that did not use machine learning, said study’s lead author Stephen Weng.

In order to evaluate the patients’ premature death, the team tested two types of AI: ‘deep learning’ AI in which layered information-processing networks help a computer to learn from examples, and a simpler ‘random forest’ AI that combines multiple, tree-like models to consider possible outcomes.

Then, the team compared the AI models’ conclusions to results from a standard algorithm, known as the Cox model. Based on these three models, the team evaluated the database of genetic, physical and health data submitted by over 500,000 people between 2006 and 2016.

During that time, around 14,500 of the participants died, primarily from heart disease, cancer, and respiratory diseases.

All the three models determined that factors like age, gender, smoking history and prior cancer diagnosis were top variables for assessing the likeliness of a person’s early death. But, the researchers found that the models diverged over other key factors.

Where the Cox model leaned greatly on ethnicity and physical activity, the machine-learning models did not. The random forest model focused more on body fat percentage, waist circumference.

Amount of fruit and vegetables people ate, and skin tone, whereas the deep-learning model emphasized on job-related hazards and air pollution, alcohol intake and the use of certain medicines.

The study co-author Joe Kai said that machine learning can be used to successfully predict mortality outcomes over time. Using AI this way ‘could help with scientific verification and future development of this exciting field’.

Ammara Khan
Author: Ammara Khan

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