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A groundbreaking AI diagnostic tool has been developed to identify autism risk in toddlers. This tool utilizes machine learning to predict Autism Spectrum Disorder (ASD) risk in children under 24 months with nearly 80% accuracy. The research, conducted by the Karolinska Institutet, highlights the potential for early intervention through noninvasive screening methods.
The study emphasizes the importance of early diagnosis and intervention, which can significantly improve developmental outcomes for children with autism. By leveraging large datasets, including the SPARK and SSC databases, the AI model named AutMedAI was created to enhance the accuracy of autism predictions. This innovative approach could revolutionize how autism is detected and treated in young children.
• AI tool predicts autism risk in toddlers with 80% accuracy.
• Early intervention is crucial for improving developmental outcomes.
The study employs machine learning to analyze autism risk factors and enhance prediction accuracy.
The AI tool aims to identify ASD risk in toddlers to facilitate early intervention.
The AI tool provides a noninvasive approach to screen for autism risk using basic medical and background information.
The institute conducted the research that led to the development of the AI diagnostic tool for autism.
The foundation's databases were crucial for training the AI model used in the study.
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