by Marisa Wexler, MS | August 5, 2024
Algorithm showed good accuracy in predicting worsening disability
A machine learning algorithm may be able to accurately predict whether or not people with multiple sclerosis (MS) will experience a worsening of disability in the near term — which may help tailor treatment decisions and improve patient quality of life — according to the findings of a new global study.
The study found that an algorithm created by its scientists had good accuracy in predicting disability progression for certain patients.
The results “support the vast potential of machine learning models for helping patients planning their lives and clinicians optimizing treatment strategies,” Edward De Brouwer, PhD, co-author of the study at KU Leuven in Belgium, said in a press release.
According to the researchers, the validation provided by the study “suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study.”
The model was described in “Machine-learning-based prediction of disability progression in multiple sclerosis: An observational, international, multi-center study,” which was published in the journal PLOS One.
Machine learning model aimed to predict near-term MS worsening
MS is a progressive disorder marked by disabling symptoms that tend to get worse with time. But the disease can manifest very differently from person to person, and it’s still very difficult to accurately predict whether any given person with MS is likely to experience worsening disability.
Thus, a team of more than 60 scientists, led by De Brouwer and Thijs Becker, PhD, of Hasselt University in Belgium, set out to predict MS disability progression using machine learning.
Machine learning is a field of artificial intelligence (AI) that basically works by feeding a large set of data into a computer, along with a set of mathematical rules that the computer can use to identify patterns in the data. This results in algorithms capable of interpreting future datasets.
For this study, the researchers used a comprehensive dataset covering more than 15,000 MS patients who were followed at 146 MS centers across 40 countries. To make the data easier to interpret, the researchers defined disability progression as a binary variable — either patients experienced confirmed disability progression within two years, or they did not.