Researchers at Baylor College of Medicine have developed a groundbreaking artificial intelligence system, AIM, to enhance the diagnosis of rare genetic disorders. The study, published in NEJM AI, showcases AIM's potential to revolutionize the identification of causative variants for Mendelian disorders.
Dr. Pengfei Liu highlighted the pressing need for improved diagnostic approaches, stating, "The diagnostic rate for rare genetic disorders is only about 30%, and on average, it is six years from the time of symptom onset to diagnosis."
Dr. Zhandong Liu emphasized the efficiency of AIM, stating, "We trained AIM to mimic the way humans make decisions, and the machine can do it much faster, more efficiently and at a lower cost. This method has effectively doubled the rate of accurate diagnosis."
The AI system also offers hope for unsolved cases, as Dr. Zhandong Liu explained, "We can make the reanalysis process much more efficient by using AIM to identify a high-confidence set of potentially solvable cases and pushing those cases for manual review."
Dr. Hugo Bellen praised AIM's capabilities, stating, "AIM is a major step forward in using AI to diagnose rare diseases. It narrows the differential genetic diagnoses down to a few genes and has the potential to guide the discovery of previously unknown disorders."
Senior author Dr. Fan Xia highlighted the impact of AIM on clinical practice, stating, "By applying real-world training data from a Baylor Genetics cohort without any inclusion criteria, AIM has shown superior accuracy. Baylor Genetics is aiming to develop the next generation of diagnostic intelligence and bring this to clinical practice."
The innovative AI system, AIM, marks a significant advancement in the field of rare genetic disorder diagnosis, offering a promising solution to expedite and enhance the accuracy of identifying these complex conditions.
