Home Health and Fitness New AI tool predicts Parkinson’s disease with 96% accuracy – 15 years in advance!

New AI tool predicts Parkinson’s disease with 96% accuracy – 15 years in advance!

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In 1991, the world was shocked to know the actor Michael J. Fox had been diagnosed with Parkinson’s disease.

A year after the release of the blockbuster Back to the Future III, he was just 29 and at the height of his Hollywood fame.Documentary this week Still: The Films of Michael J. Fox will be released. It features interviews with Fox, his friends, family and experts.

Parkinson’s disease is a debilitating neurological disorder that: motor symptoms Slowness of movement, body tremors, muscle stiffness, loss of balance, etc.Fox is already broken I fell many times and injured my arm, elbow, face and hand.

It is not genetic, there are no specific tests, and it cannot be accurately diagnosed before motor symptoms appear.The cause is i don’t knowFox is one of those who thinks so, though. Chemical exposure may play a central rolespeculates that “genes load the gun and the environment pulls the trigger.”

In a study published today, ACS Central Sciencehas built an artificial intelligence (AI) tool that can predict Parkinson’s disease with up to 96% accuracy up to 15 years before clinical diagnosis, based on the analysis of chemicals in blood.

While this AI tool showed promise for accurate early diagnosis, it also revealed chemicals strongly associated with correct predictions.

more common than ever

Parkinson’s disease worldwide The fastest growing neurological disease and 38 Australian Diagnosed daily.

The likelihood of developing Parkinson’s disease in people over the age of 50 is higher than most cancers Includes breast cancer, colorectal cancer, ovarian cancer, and pancreatic cancer.

symptoms such as depression, olfactory disorder, sleep disorder It can predate clinical behavior and cognitive symptoms by decades.

However, the prevalence of such symptoms in many other medical conditions means that early signs of Parkinson’s disease may be missed and management of the condition may be mismanaged, leading to increased hospitalization rates and effectiveness. This means that it may contribute to therapeutic strategies without

our research

UNSW collaborated with Boston University experts to develop a mass spectrometry dataset ( technology Detects chemicals from blood samples.

In this study, we examined Spanish. European prospective study on cancer and nutrition (EPIC) Studies with more than 41,000 participants. About 90 of them developed Parkinson’s disease within 15 years.

To train the AI ​​model, we used data subset It consisted of randomly selected 39 participants who later developed Parkinson’s disease. They were matched with 39 control participants who did not. The AI ​​tool was provided with blood data from participants who were all healthy at the time of blood donation. This meant that blood could provide early signs of disease.

Based on blood data from the EPIC study, we conducted 100 “experiments” using AI tools to assess the accuracy of 100 different models for predicting Parkinson’s disease.

Overall, AI can detect Parkinson’s disease with up to 96% accuracy. The AI ​​tool was also used to identify which chemicals and metabolites are likely to be associated with later disease development.

major metabolite

Metabolites are chemicals produced or used when the body digests and breaks down foods, drugs, and other substances upon exposure to the environment.

Our bodies may contain thousands of metabolites, the concentrations of which can vary greatly between healthy and diseased individuals.

Our study identified chemicals, presumably triterpenoids, as key metabolites that could prevent Parkinson’s disease. People with Parkinson’s disease have lower levels of triterpenoids in their blood than those without.

Triterpenoids are known neuroprotective agent can be regulated oxidative stress – a major factor involved in Parkinson’s disease – and prevents cell death in the brain.many foods such as apple and tomato Rich source of triterpenoids.

Synthetic chemicals ( polyfluorinated alkyl substance) were also linked as potentially increasing disease risk. This chemical was found more often in people who later developed Parkinson’s disease.

Further studies using different methods and examining larger populations are needed to further validate these results.

High financial and personal burden

In Australia, the average person with Parkinson’s disease spends $14,000 Self-pay for medical expenses.

The burden of living with an illness can become overwhelming.

Fox admits the disease can be a “nightmare” and a “living hell,” but he also found that:With gratitude, optimism is sustainable”.

As researchers, we are hopeful about the potential use of AI technology to improve patients’ quality of life and reduce healthcare costs by accurately detecting disease early.

We look forward to the research community trying out our AI tools. It has been published.

This research was conducted with Chonghua Xue and Professor Vijaya Kolachalama (Boston University).conversation

article written by Diana ChanFulbright and Scientia Postdoctoral Fellows, Sydney, New South Wales and William Alexander DonaldAssociate Professor, ARC Future Fellow, UNSW Scientist Fellow, Sydney, New South Wales

This article is reprinted from conversation Under Creative Commons License.read Original work.

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