Artificial intelligence (AI) can rapidly diagnose Alzheimer’s disease and improve prognosis, a new study has revealed. Alzheimer’s disease is a neurological disorder in which the death of brain cells causes memory loss and cognitive decline.
Scientists at the Neuroscience Institute of the University of Sheffield, UK, investigated how regular use of AI in health care can help reverse time and economic impacts, such as common neurodegenerative diseases such as Alzheimer’s and Parkinson’s, the National Health Service (NHS) ).
The main risk factor for many neurological disorders is age, and populations around the world are living longer than ever before, with the potential for an unprecedented level of decline in the number of people with a neurodegenerative disease. The study said that the number of people living alone with Alzheimer’s is estimated to reach 115 million by 2050.
The study, published in the journal Nature Review Neurology, described how AI techniques, such as machine learning algorithms, can detect neurodegenerative disorders – causing part of the brain to die – before progressive symptoms worsen. This may improve the likelihood that patients will benefit from successful disease-modifying treatments.
The lead author of the study, Dr. from the University of Sheffield. Laura Ferraiolo said: Most neurodegenerative diseases are still untreated and in many cases are diagnosed late due to their molecular complexity. For example, widespread implementation of AI technologies may help, predicting whether patients with mild cognitive impairment will go on to develop Alzheimer’s disease or how severe their motor skills will decline over time.
AI-powered technologies can be used to help patients overcome their symptoms and the privacy of their homes, which will be of huge benefit to patients with mobility issues.
Machine learning algorithms can be trained to identify changes caused by medical images, patient movement information, speech recordings or footage showing a patient’s behavior, making AI a valuable diagnostic aid.
For example, it can be used by trained professionals in radiology departments to analyze images more quickly and uncover important results for immediate follow-up.
Algorithms can also listen to patients’ speech and analyze their vocabulary and other semantic features to assess their cognitive function. Machine learning can also use information contained within electronic health records or genetic profiles to suggest the best treatment for individual patients.
Another scientist at the University of Sheffield, Monica Myshezinska, said: “It is too early to talk about outcomes in terms of treatment but, in this study, we investigated how to use machine learning methods to identify the best course of treatment Can be done. Depending on their disease progression, or how they can be used to identify new therapeutic targets and drugs.