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

<b>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.</b>自闭症谱系障碍（Autism Spectrum Disorder，ASD）是一种受多种遗传与环境因素共同影响的复杂神经发育障碍。目前尚无用于其早期诊断的确定性临床检测手段，例如血液分析或脑部扫描。本研究旨在开发一款计算模型，利用基因组数据预测早期阶段的自闭症谱系障碍致病驱动基因，以期提升早期诊断与干预的效能。