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Study Shows Osteoarthritis Can Be Diagnosed by AI Years Before Onset

MD News Daily - Study Shows Osteoarthritis Can Be Diagnosed by AI, Cartilage Texture Analyzed Years Before Onset
(Photo : Angelo Esslinger on Pixabay)
A study recently showed that artificial intelligence or AI could diagnose Osteoarthritis by analyzing cartilage texture there years before it begins to wear away and cause joint pain.



A study recently showed that artificial intelligence or AI could diagnose Osteoarthritis by analyzing cartilage texture there years before it begins to wear away and cause joint pain.

The John Hopkins Hospital researchers and others in the field ran an AI model over scans of more than 80 individuals who do not have noticeable symptoms of osteoarthritis.

According to research, the machine learning model discovered the onset stages of Osteoarthritis with 78-percent accuracy of a maximum of three years before the beginning of the symptoms.

Reports have it that in the United Kingdom, roughly 8.5 million people suffer from this condition, which results in joints turning stiff and painful, specifically among individuals with more than 65 years of age.

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Early Detection Can Delay the Onset of Symptoms

According to the study authors, if Osteoporosis can be detected early, weight loss and exercise, combined, could make the condition less severe upon its occurrence. The combination can even delay the start of symptoms.

This research also indicates that several illnesses, including osteoarthritis, don't have any apparent cues in the early phases eluding image-based detection like MRI or x-ray.

For Osteoarthritis, by the time the condition is detected, it is at an irreparable or permanent stage-well-following bone impairment and has been caused already.

Researchers said the present treatment focuses on "palliative care or invasive" and expensive surgery and incorporated with other "musculoskeletal conditions cost the NHS roughly $13 billion each year.

According to the NHS, as Osteoarthritis mainly affects older individuals and the population gets older, it is believed that the amount could rise to roughly more than $150 in the next ten years.

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AI's Ability to Spot Early Signs of Osteoarthritis

This new approach, which the US scientists developed, will enable doctors to spot early signs of Osteoarthritis developing even before it turns out to be a permanent illness.

Additionally, the researchers used AI to search for more "patterns in MRI scan images that could even allow" for the digital discovery of impairment or damage in cartilage maps in the future.

In their research, the study authors specified that symptomatic osteoarthritis in the future could potentially be projected up to three years before the "current standard diagnosis."

Furthermore, the researchers investigated the cartilage in healthy individuals through the use of AI. They developed a diagnostic system that seems to be able to foretell the early stage of the condition.

The current study has limitations as it was based on a limited group of 86 participants, and a machine-learning model is benefiting from what the researchers say, "As large as a pool as possible."

The research team explained, with increasing size of the sample, machine-learning approaches turn out to be more vigorous to differences that may exist within a particular populace.

A Vital Step Ahead

As there is currently no dependable method to discover and identify pre-symptomatic osteoarthritis at the potentially alterable early stages, this new system could be vital.

Detecting it before it begins damaging the joints, according to the team, future treatments could be developed that may even stop the illness from staying.

More research, though, the study authors said, is needed before this approach could be utilized or applied in a clinical setting, which includes extensive research to test the artificial intelligence model; the bigger sample size will determine uncommon variations.

Scientists said they want to do tests as well, "that compare actual cartilage chemical conditions" predictions of the AI model to guarantee that they are precise.

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