AI In Medicine: University of Louisville Develops New AI Platform That Can Diagnose Autism Much Earlier And With 98.5 Percent Accuracy!
Nikhil Prasad Fact checked by:Thailand Medical News Team Nov 25, 2023 8 months, 1 day, 13 hours, 18 minutes ago
AI In Medicine: In a monumental stride forward for medical science, the University of Louisville in Kentucky, USA, has introduced an unprecedented artificial intelligence (AI) system capable of diagnosing autism in children aged 24 to 48 months with a staggering accuracy rate of 98.5%.
This groundbreaking research covered in this
AI In Medicine report, signifies a quantum leap in the timely and accurate identification of autism, offering promising prospects for early intervention and enhanced developmental outcomes.
The brainchild of a collaborative effort led by Mohamed Khudri, B.Sc., a visiting research scholar at the University of Louisville, the three-stage AI system focuses on the analysis of diffusion tensor MRI (DT-MRI) scans of the brain. DT-MRI, a specialized imaging technique, meticulously tracks the movement of water along white matter tracts in the brain, providing a detailed understanding of neural connectivity. The AI system, designed with precision, isolates brain tissue images from these scans and extracts imaging markers indicative of the level of connectivity between different brain regions.
Khudri articulates the core functionality, stating, "Our algorithm is trained to identify areas of deviation to diagnose whether someone is autistic or neurotypical." This innovative approach capitalizes on the recognition that autism fundamentally manifests as improper connections within the brain. Dr Gregory N. Barnes, M.D., Ph.D., co-author and director of the Norton Children's Autism Center in Louisville, elucidates that DT-MRI adeptly captures these abnormal connections responsible for the hallmark symptoms associated with autism, including impaired social communication and repetitive behaviors.
The robustness of the AI system was put to the test through a rigorous evaluation of its methodology using DT-MRI scans from the Autism Brain Imaging Data Exchange-II. This comprehensive dataset encompassed scans from 226 children aged 24 to 48 months, including 126 diagnosed with autism and 100 typically developing children. The results were nothing short of remarkable, with the AI system demonstrating a remarkable 97% sensitivity, 98% specificity, and an overall accuracy rate of 98.5% in identifying children with autism.
One of the pivotal strengths of this AI system lies in its potential to enable the early detection of autism in infants under two years of age. Khudri underscores the significance, noting the potential for therapeutic intervention before the age of three, which holds the promise of significantly improved outcomes, including greater independence and higher IQs for individuals with autism.
Against the backdrop of the CDC's 2023 Community Report on Autism, which highlights that less than half of children with autism spectrum disorder undergo a developmental evaluation by the age of three, and 30% of those meeting the criteria for autism spectrum disorder do not receive a formal diagnosis by the age of eight, the urgency for early intervention becomes even more pronounced.
Delays in diagnosis can be attributed to various factors, including a lack of resources and bandwidth at testing centers.
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Dr Barnes accentuates the critical importance of early intervention, emphasizing the leverage of the brain's plasticity - the ability to normalize function through therapy. The AI system not only facilitates precise autism management but also holds the potential to significantly reduce the time and costs associated with assessment and treatment. The researchers envision a streamlined assessment process, commencing with DT-MRI, followed by a concise session with a psychologist to confirm results and guide parents on the next steps. This innovative approach has the potential to alleviate psychologists' workload, potentially reducing it by up to 30%.
Beyond its diagnostic capabilities, the AI system generates a comprehensive report detailing the specific neural pathways affected, the anticipated impact on brain functionality, and a severity grade. This detailed information becomes instrumental in guiding early therapeutic intervention, tailoring treatments to the unique needs of each child.
As the research progresses, the University of Louisville's team is actively working towards commercializing and obtaining FDA clearance for their AI software. This crucial step towards making the technology widely accessible marks a significant milestone in the translation of groundbreaking research into real-world applications.
In conclusion, the unveiling of the University of Louisville's AI system represents a paradigm shift in the landscape of autism diagnosis. With unparalleled accuracy and the potential for early intervention, this technology holds the promise of transforming the lives of individuals with autism and reshaping the landscape of healthcare delivery. The Radiological Society of North America (RSNA) serves as the stage for the revelation of this monumental achievement, underscoring the pivotal role of AI in revolutionizing medicine and advancing our understanding and treatment of neurodevelopmental disorders.
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