An automated detection system of autism spectrum disorder using meta-heuristic approach of adaptive LSTM with bayesian learning technique

Key Points

• The system demonstrates high accuracy in identifying autism spectrum disorder, enhancing early detection.
• Key metrics reveal an accuracy rate of 92% when applying the adaptive LSTM model.
• The method employs a meta-heuristic approach using Bayesian learning techniques to improve performance.
• This research supports ongoing efforts in developing reliable automated tools for diagnosing autism spectrum disorder.