Predicting Mortality : AI Model By Danish Researchers Estimate Life Span and Predict Death

In Denmark, researchers are using the full potential of AI and data collected from millions of individuals to navigate the various stages of a person’s life and build a conclusion. Their motive is to throw light on both capabilities and potential risks related to this advanced technology. The makers of life2vec are driven by a curiosity to disclose patterns and correlations that deep-learning algorithms, known for their capacity to delve into complex data sets, might reveal. Their goal is to develop a predictive tool capable of foreseeing a broad spectrum of health and social milestones.

“It’s a very general framework for making predictions about human lives. It can predict anything where you have training data,” said Sune Lehmann, who is a professor at the Technical University of Denmark and is also one of the authors of a study recently published in the journal Nature Computational Science.

For Lehmann, one of the minds behind the project, the scope of possibilities appears boundless. She emphasized the potential of the AI model to forecast diverse health outcomes. “It could predict health outcomes. So it could predict fertility or obesity, or you could maybe predict who will get cancer or who doesn’t get cancer. But it could also predict if you’re going to make a lot of money,” she explained. Moreover, Lehmann highlighted the algorithm’s capacity to predict socioeconomic factors, such as financial success.

Operating on a methodology which is similar to that of ChatGPT, the algorithm takes the plethora of life-influencing variables into consideration, including birth circumstances, educational background, social support systems, and even occupational routines. Through this elaborate analysis, researchers aim to construct a predictive framework capable of offering insights into life’s trajectory, empowering individuals with knowledge about potential future events and circumstances.