Scientists assert that it is currently impossible to determine the exact date of one’s death with reliability. Nonetheless, they have developed algorithms aimed at addressing this challenge. Among these advancements is a contribution from British researchers who have programmed a neural network to assess death risks and estimate its timing.
The “death calculator,” known as AIRE, is an advanced artificial intelligence model that analyzes electrocardiograms (ECGs) to identify the risk of cardiovascular disease years before symptoms manifest. The Lancet journal published information about this development.
The study states, “AIRE accurately predicts the risk of all-cause mortality.”
Early on, AI can detect heart failure, arrhythmias, and other conditions, and forecast changes in heart structure and function by analyzing genes linked to biological aging and metabolic syndrome.
Researchers believe that neural networks are sufficiently trained to diagnose common diseases accurately. By assessing and comparing numerous factors, they can estimate risks and timelines.
AIRE has been proven to predict short- and long-term mortality risks from a single ECG accurately. It has been tested in the USA, Brazil, and the UK, with about 1.6 million ECGs from patients of varying ages and health statuses reviewed. The medical community has expressed satisfaction with its performance.
Research indicates that AIRE can predict death risks within ten years with 78% accuracy, and even higher precision for individuals with heart disease.
Neural networks have shown high accuracy in predicting mortality over various time frames, proving to be significantly more precise than traditional methods of mortality forecasting. The researchers emphasize the growing importance of ECG risk prediction, especially as the ability to perform electrocardiograms becomes more widespread, including consumer versions. For instance, certain AIRE models are now implementable in smartwatches.
“The goal wasn’t to replace doctors but to create something that could perform superhuman tasks,” the scientists stated.
The Daily Mail reports that starting from mid-next year, this technology will undergo further testing in two London hospitals. Experts are hopeful that within five years, the technology will be so prevalent that every medical institution in Britain will have access to it.
Researchers continue to highlight that cardiovascular diseases are the leading cause of death globally. The Centers for Disease Control and Prevention (CDC) report that in the United States, cardiovascular disease claims a life every 33 seconds, with over 702,000 deaths in 2022. In the Russian Federation, cardiovascular diseases account for approximately one million deaths annually.
There have been similar advancements in the field of medicine already.
For instance, the Danish-American AI model Life2vec examines a range of data to generate predictions. To estimate the potential date of death, factors such as age, profession, health data, and income are required. A neural network was tested on the data of approximately six million Danes, revealing that the likelihood of an accurate prediction is high, at 79%.
Another advancement is attributed to Chinese researchers. Their neural network can forecast outcomes using 175,000 different parameters, such as scanned old certificates, extracts, and other medical data. If the diagnosis is known, it can predict the date of death with a precision of up to one month.
