Artificial Intelligence Rapidly Diagnoses Rare Disorders

Artificial Intelligence Rapidly Diagnoses Rare Disorders
Artificial intelligence is proving to be the new phase of medicine, where technology helps clinicians determine the root cause of disease sooner.
Technology Briefing


Artificial intelligence is also proving to be highly accurate in rapidly diagnosing rare disorders in critically ill children. The benchmark finding, published in the journal Genomic Medicine, foreshadows the new phase of medicine, where technology helps clinicians quickly determine the root cause of disease so they can give patients the right treatment sooner. Worldwide, about seven million infants are born with serious genetic disorders each year. For these children, life usually begins in intensive care.

In the most advanced hospitals teams search for genetic causes of their disease by sequencing, the three billion DNA letters that make up the human genome. Today, it takes hours to sequence the whole genome and then it can take days or weeks of computational and manual analysis to diagnose the illness. For some infants, that is not fast enough. Yet, understanding the cause of the newborn’s illness is critical for effective treatment. So, arriving at a diagnosis within the first 24 to 48 hours after birth gives these patients the best chance to improve their condition. Knowing that speed and accuracy are essential, researchers worked to develop the new Fabric GEM algorithm, which incorporates AI to find DNA errors that lead to disease.

In the new study, the scientists tested GEM by analyzing whole genomes from 179 previously diagnosed pediatric cases from six medical centers around the world. GEM identified the causative gene as one of its top two candidates 92% of the time. By doing so it outperformed existing did so in 60% of the time. GEM algorithm leverages AI to learn from a vast and ever-growing body of knowledge that has become increasingly challenging for clinicians and scientists to keep up with. GEM cross-references large databases of genomic sequences from diverse populations, clinical disease information, and other repositories of medical and scientific data, combining all this with the patient’s genome sequence and medical records.

To assist with the medical record search, GEM is coupled with a natural language processing tool, which scans reams of doctors’ notes for the clinical presentations of the patient’s disease. Critically ill children rapidly accumulate many pages of clinical notes. The need for physicians to manually review and summarize note contents as part of the diagnostic process is a massive time sink. The ability of the natural language processing tool, to automatically convert the contents of these notes in seconds for consumption by GEM is critical for speed and scalability.

Existing technologies mainly identify small genomic variants that include single DNA letter changes, or insertions and deletions of small strings of DNA letters. By contrast, 35 OCTOBER 2021 GEM can also find “structural variants” which causes disease. These changes are larger and are often more complex. And it’s estimated that structural variants are behind 10 to 20% of genetic disease. To be able to diagnose with more certainty opens a new frontier because these advances now provide an explanation for why a child is sick, enable doctors to improve disease management, and, at times, lead to recovery. This is a major innovation only made possible because of AI.


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