Artificial intelligence (AI) has proven to be an important ally in the diagnosis of Autism Spectrum Disorder (ASD). Recent studies use convolutional neural networks to analyze brain images and identify patterns associated with ASD. These AI systems are trained on thousands of images to recognize variations that may go unnoticed by traditional methods.
AI's main advantage is its ability to process large volumes of data with accuracy and speed. In the context of autism, this means earlier and more objective identification of neurological signs related to the condition. This approach can complement clinical diagnosis and offer support to health professionals.
As technology advances, artificial intelligence is expected to become increasingly accessible in clinical practice. Although it is still in the testing phase in many places, the use of AI represents a major step toward more accurate and personalized diagnoses.
Reference: Adhikary, A. (2023). “Identification of Novel Diagnostic Neuroimaging Biomarkers for Autism Spectrum Disorder Through Convolutional Neural Network-Based Analysis”. arXiv preprint arXiv:2305.18841. Available at: https://arxiv.org/abs/2305.18841