eNSMBL-PASD: Spearheading Early Autism Spectrum Disorder Detection through Advanced Genomic Computational Frameworks Utilizing Ensemble Learning Models

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition influenced by various genetic and environmental factors. Currently, there is no definitive clinical test, such as a blood analysis or brain scan, for early diagnosis. The objective of this study is to develop a computational model that predicts ASD driver genes in the early stages using genomic data, aiming to enhance early diagnosis and intervention.