The Michael J. Fox Foundation, created by the actor of the same name who played Marty McFly in the “Back to the Future” movie series, has published an article in which it shows an artificial intelligence (AI) model capable of predicting symptom progression of Alzheimer’s.
The survey, carried out in partnership with IBM, was disclosed at the end of July in the scientific magazine The Lancet Digital Health.
Michael J. Fox announced he had the disease in 1998 but had been diagnosed seven years earlier when he was 29 years old. The foundation was created in 2000 as part of the actor’s efforts to help people who suffer from the same condition – it is estimated that today more than six million individuals have Parkinson’s.
Parkinson’s is characterized by hand tremor. However, other symptoms can appear from this degenerative condition, such as sluggishness and stiffness of the limbs, and loss of balance. It is a disease that affects the central nervous system and is caused by a progressive and intense decrease in the production of dopamine, a neurotransmitter that helps nerve cells communicate.
The challenge for scientists is to understand how the disease starts and what treatments are most effective — but this is no easy task. As the researchers themselves point out, Parkinson’s has a variable progression of symptoms in all patients, which makes this work difficult.
The model that uses artificial intelligence and machine learning comes to solve exactly this problem, grouping the data and offering an alternative to combat the progressive evolution of the disease.
The use of AI comes to support what doctors call patient management and clinical trial design. The model created based on machine learning is able to predict the progression of symptoms (motor and non-motor) in terms of time and severity.
The technology uses as learning what scientists call longitudinal patient data, which represents a description of the clinical condition of someone who suffers from Parkinson’s over time. The researchers hope that using this model will be able to offer clinicians a new tool to predict disease progression.
The institutions involved in the research claim that the use of this technology will allow better management of the disease’s treatment. As a result, researchers will be able to more confidently identify candidates for more specific and effective clinical trials for each disease condition.