Predictive Analytics and AI for Early Diagnosis and Intervention in Autism Spectrum Disorders

Predictive analytics and AI being investigated to see whether they may aid in the early diagnosis of autism spectrum diseases. The suggested method, entitled “Behavioral Biomarker Identification (BBI),” makes use of machine learning algorithms to spot patterns of behavior that may be suggestive of autism spectrum disorder (ASD). Some popular examples of such algorithms are random forests, logistic regression, and deep neural networks (DNNs). Six other common techniques are compared to BBI to see if it is more effective. Research has shown that BBI is more effective, sensitive, and specific than competing methods. Those with autism spectrum condition can now be diagnosed with more certainty and accuracy thanks to this approach. The BBI's potential as a tool for early identification of autism spectrum disorders is supported by its improved accuracy compared to conventional approaches. The high sensitivity of the BBI (88%), which assures a limited level of false negatives, is essential for effectively detecting instances of ASD. Its specificity of 94% is great for eliminating false positives by excluding situations that have nothing to do with ASD. Data privacy and ethical considerations are prioritized in the proposed approach, which addresses them with openness and strict security measures. This ensures that all patient data is handled in a lawful and transparent way. The BBI approach represents a giant leap forward in the quest to diagnose autistic diseases. Artificial intelligence and predictive analytics enable earlier diagnosis of autism spectrum disorder and hence earlier intervention. BBI is a helpful tool for healthcare professionals because it is more accurate and sensitive than traditional approaches, and because it prioritizes data protection and ethical principles, further assuring its responsible deployment in clinical situations. This study demonstrates that the quality of life for people with autism spectrum disorder (ASD) might be considerably enhanced via the use of artificial intelligence (AI) and predictive analytics. Research and therapy for autism spectrum disorder (ASD) might benefit greatly from the BBI approach due to its high efficacy and lack of ethical considerations.