New AI methodologies integrate imaging and genomic data to enhance disease diagnosis and prognostics. Osaka Metropolitan University researchers developed an AI model to detect fatty liver disease noninvasively from chest X-rays, leveraging large retrospective datasets with clinical annotations. Additionally, studies demonstrate that whole-genome and exome sequencing, recommended as first-tier for pediatric rare diseases and developmental delays, improve diagnostic yields and outcomes. These technological integrations present a promising shift towards precise, scalable, and accessible diagnostics.