A deep learning model for prediction of autism status using whole-exome sequencing data.

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This study shows that advanced computer models can use a child’s genetic information to help estimate the likelihood of autism, offering hope that families affected by 16p11.2 may one day benefit from earlier, more precise genetic screening to guide diagnosis and support—though this approach is not yet ready for everyday clinical use.