A new method developed by Ben-Gurion University of the Negev (BGU) in Beersheba and Mount Sinai Hospital in New York uses machine learning to identify and detect disease risk, health conditions and biological age.
As health funds in Israel are more accessible, many Israelis go to their family doctor with complaints about various sensations or as part of a periodic examination and receive a referral for blood tests.
It turns out that the amount of laboratory tests performed in Israel is significantly greater compared to any other Western country.
Although these tests are available and allow for quick and consistent information tracking regarding patients, they are often tested according to a method that detects only results that deviate from the norm.
Machine learning can make it possible, however, to locate abnormal results of medical tests that may indicate a possible disease by locating and comparing all the results together and to the entire population and not just by referring to the abnormal result.
How does this new strategy work?
Even if each of the results of the various tests is within the normal range, there is still a certain combination that can indicate an abnormal result, according to the researchers, Dr. Nadav Rappoport of the BGU Department of Software and Information Systems Engineering (lead author), as well as students Bar Ezra and Lynn Peretz. They worked along with Shreyas Havaldar and Benjamin Glicksberg from Mount Sinai Hospital in New York.
Biological age may be more important than chronological age, and they can be estimated using machine learning for common laboratory tests, for example. The model was able to closely predict the true age of the specimen with an average error of more or less six years.
The researchers examined the health of individuals who had a discrepancy between their biological age and their actual age and showed that subjects for whom the model predicted an age younger than their actual age were found to be healthier than expected, as they had fewer diagnoses, fewer surgeries and a lower incidence of specific diseases compared to an age-matched control group.
But for subjects who were predicted to be older than their chronological age, there were no significant differences in the number of diagnoses, the number of surgeries and specific diseases compared to an age-matched control group. The researchers showed that people with abnormal results at the global level have a higher chance of being hospitalized and getting sick in general.
The researchers even built a model that predicts biological age using the results of common blood tests and was able to show that people with a biological age lower than the chronological age are healthier.
Using the results of laboratory tests taken from the human biological sample bank of the British Biobank, approximately 500,000 subjects aged 37 to 82 were examined.
The results of the studies were confirmed at Mount Sinai Hospital. There, the researchers looked at about 100,000 periodic doctors (wellness) visits during which lab tests were taken. The results were similar to those the researchers found in the British database.
There are currently tests for biological age estimation by sequencing the DNA ends or by testing epigenetic markers, but they are expensive, complicated, take a long time and require a dedicated sample collection, so the majority of the population will not be entitled to undergo this test – certainly not frequently.
A computational model based on lab tests such as the one that the researchers propose makes it possible to obtain a personal health status picture for each applicant at a low cost and in a relatively short time even as an additional result of the laboratory tests that are done following various indications.
“To determine health status is no small matter,” concluded Rappoport. “We looked at both the specific level of each disease and at data independent of the disease, and the information we produce will allow patients to know their health status to improve or maintain their lifestyle.”
“We looked at both the specific level of each disease and at data independent of the disease, and the information we produce will allow patients to know their health status to improve or maintain their lifestyle.”
Dr. Nadav Rappoport
They presented their findings at the Medical Informatics Europe (MIE) conference in Nice, France, in May, and just published two studies in PubMed of the US National Center for Biotechnology Information of the National Library of Information of the US National Institutes of Health under the titles “Multi-Dimensional Laboratory Test Score as a Proxy for Health” and “Deviation of Physiological from Chronological Age Is Associated with Health.”