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Neuropsychology Meets AI

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Artificial intelligence (AI) has been becoming a subject of many fields over time. Whether it will be capable of doing anything human beings can do or not is a big part of the arguments (Artificial General Intelligence -- AGI). On the other side, Artificial Narrow Intelligence (ANI) which comprehends some capabilities not only becomes more reliable in those capabilities but also expands its frame (i.e. Machine learning (ML) which is a vital tool for AI makes supervised learning possible. As a basic example, AI for self-driving cars needs huge data for better performance in determining which is a car and which is not, to keep optimum distance in traffic.


Using GPUs to Discover Human Brain Connectivity - Neuroscience News

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Summary: Researchers developed a new GPU-based machine learning algorithm to help predict the connectivity of networks within the brain. A new GPU-based machine learning algorithm developed by researchers at the Indian Institute of Science (IISc) can help scientists better understand and predict connectivity between different regions of the brain. The algorithm, called Regularized, Accelerated, Linear Fascicle Evaluation, or ReAl-LiFE, can rapidly analyse the enormous amounts of data generated from diffusion Magnetic Resonance Imaging (dMRI) scans of the human brain. Using ReAL-LiFE, the team was able to evaluate dMRI data over 150 times faster than existing state-of-the-art algorithms. "Tasks that previously took hours to days can be completed within seconds to minutes," says Devarajan Sridharan, Associate Professor at the Centre for Neuroscience (CNS), IISc, and corresponding author of the study published in the journal Nature Computational Science.


How this AI tool can detect Alzheimer's by analyzing subtle linguistic patterns

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We may be one step closer to an artificial intelligence (AI) tool capable of diagnosing Alzheimer's disease faster and more accurately, according to a new study conducted by Stevens Institute of Technology. "This is a real breakthrough. We're opening an exciting new field of research, and making it far easier to explain to patients why the A.I. came to the conclusion that it did, while diagnosing patients. This addresses the important question of trustability of A.I .systems in the medical field," said K.P. Subbalakshmi, the lead researcher. The new AI tool involves the analyzation of subtle linguistic patterns characteristic of people with a neurodegenerative disease.


Artificial intelligence may diagnose dementia as accurately as clinicians

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To solve the conundrum of how to get timely medical care to people with memory loss or other impaired cognitive functioning, a new study suggests that artificial intelligence may be as accurate as clinicians in taking the first step: diagnosis. Findings from the study, which was conducted by researchers at Boston University School of Medicine, were published online Monday in the journal Nature Communications. "We're trying to leverage AI to create frameworks to mimic neurology experts," for dementia diagnosis, Vijaya B. Kolachalama, the study's principal investigator and assistant professor of medicine and computer science at Boston University, told UPI. He said his lab aims to use computer models to assist clinical practice. Kolachalama stressed that the aim of his team's work is to help reduce the workload of the busy neurology practice, not replace the expert clinician.


Dementia breakthrough: Simple brain scan can detect early-stage Alzheimer's with 98% accuracy

Daily Mail - Science & tech

A simple brain scan can detect people with early-stage Alzheimer's disease, a study suggests. In what could be a breakthrough, researchers have developed an algorithm that can diagnose the condition with up to 98 per cent accuracy. The computer programme uses standard MRI technology found in most hospitals to produce a result in 12 hours. Currently it can take months to diagnose the disease on the NHS and requires a raft of memory and cognitive tests as well as scans. Researchers from Imperial College London who developed the algorithm, which was tested on more than 400 people, hope it will be rolled out on the NHS by 2025.


Drawing a Better Picture of Global Cognition in Older Adults

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Tsukuba, Japan--Cognitive impairments, like those that eventually lead to Alzheimer's disease, have large social and economic impacts and often decrease people's quality of life. They're also relatively underdiagnosed, partly because their diagnosis relies on clinical tests, which aren't always easy to access. In a study published last month in JMIR Formative Research, researchers from the University of Tsukuba, University of California San Diego, and IBM Research have revealed that they could estimate global cognition in older adults from both Japan and the USA by automatically analyzing key drawing features while a drawing task was performed using a digital pen and tablet. Only about 25% of all dementia cases receive a diagnosis worldwide, and this percentage is even lower in developing countries. To add to this problem, access to cognitive screening was difficult during much of the COVID-19 pandemic.


AI-based speech pattern analysis may allow Alzheimer's diagnosis by phone

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Patterns of speech in a phone conservation can be used to correctly identify adults in the early stages of Alzheimer's disease, a study published Wednesday by the journal PLOS found. Using more than 1,600 voice recordings of phone conversations made from 24 people with confirmed Alzheimer's and 99 healthy controls, researchers correctly identified those with the common form of dementia with roughly 90% accuracy, the data showed. The approach relies on the tendency of people with Alzheimer's "to speak more slowly and with longer pauses and to spend more time finding the correct word," the researchers said. These "vocal features" result in "broken messages and lack of speech fluency," which can be analyzed using an artificial intelligence-based program. The computer program was able to identify those with early Alzheimer's with essentially the same level of accuracy as a telephone-based test for cognitive function, according to the researchers.


Fujifilm develop AI technology that can predict the progression of Alzheimer's

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Fujifilm and the National Center of Neurology and Psychiatry (NCNP) have just released new research which shows that AI technology could help to predict whether or not someone is likely to get Alzheimer's disease. By monitoring brain activity, Fujifilm and NCNP say that they are able to predict whether a patient with mild cognitive impairment (MCI) will progress to having dementia within two years with an accuracy of up to 88%. Alzheimer's disease is the most common cause of dementia and it is estimated that 55 million people worldwide have the neurological condition that causes loss of memory. As the population ages, it's expected that by 2050, more than 139 million people will suffer from the life-changing condition. Using advanced image recognition technology, Fujifilm and NCNP have developed a way in which they are able to monitor the progression of Alzheimer's from three-dimensional MRI scans of the brain.


Covid lockdown made people more creative, study says

Daily Mail - Science & tech

Whether it was doing the kitting or learning to play a new instrument, the Covid lockdown made people more creative, a new study says. Researchers in Paris have surveyed hundreds of people about activities performed during the first lockdown at the start of the pandemic more than two years ago. Overall, based on almost 400 responses, the team found that people were forced to adapt to a new situation and'rethink our habits', which bred creativity. The researchers also acknowledged that pandemic and stay-at-home rules'restricted our liberties and triggered health or psychological difficulties', however. The new study has been led by researchers from the Frontlab at the Paris Brain Institute in France and published in Frontiers in Psychology.


Using AI to diagnose mild cognitive impairment that progresses to Alzheimer's

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Alzheimer's disease is the main cause of dementia worldwide. Although there is no cure, early detection is considered crucial for being able to develop effective treatments that act before its progress is irreversible. Mild cognitive impairment is a phase that precedes the disease, but not everyone who suffers from it ends up developing Alzheimer's. A study led by scientists at the Universitat Oberta de Catalunya (UOC) and published in the IEEE Journal of Biomedical and Health Informatics, has succeeded in precisely distinguishing between people whose deterioration is stable and those who will progress to having the disease. The new technique, which uses specific artificial intelligence methods to compare magnetic resonance images, is more effective than the other methods currently in use. Alzheimer's disease affects more than 50 million people worldwide, and the aging of the population means that there may be many more sufferers in the coming decades.