ASHG will host the Genetic Diagnosis & Rare Disease Virtual Symposium on December 2–3, featuring 16 expert-led sessions on cutting-edge genomic technologies and rare disease diagnosis. The event offers interactive learning, up to six CME credits, and global access to innovations like long-read sequencing, RNA-Seq, and federated variant sharing.

Medical reports written in technical terminology can pose challenges for patients. A team at the Technical University of Munich (TUM) has investigated how artificial intelligence can make CT findings easier to understand. In the study, reading time decreased, and patients rated the automatically simplified texts as more comprehensible and more helpful.

A comprehensive review and perspective on differentiable imaging—a paradigm pioneered by research team since 2021—shows how systematic uncertainty quantification has revolutionized computational imaging and proposes how digital twin integration could enable fully autonomous, self-optimizing systems. The paper in Advanced Devices & Instrumentation, by Dr. Ni Chen (HKU), Professor David J. Brady (University of Arizona), and Professor Edmund Y. Lam (HKU), both reviews the field's rapid progress and charts its evolution toward intelligent adaptive systems.