Pioneering AI-based approach identifies rare disease patients using electronic health records ArtificialIntelligence AI MachineLearning PompeDisease FrontNeurol
By Dr. Priyom Bose, Ph.D.May 11 2023Reviewed by Benedette Cuffari, M.Sc. Rare diseases are defined as those that occur in one for every 2,000 people in the European Union and less than 200,000 people in the United States each year. To date, about 7,000 RDs have been identified; however, the diagnosis of RDs remains a challenge.
Typically, it takes between 2.5 months and 144 months to correctly diagnose Pompe disease. Estimation methods based on genetic databases have indicated that Pompe disease prevails in one in every 23,232 individuals. However, survey-based investigations, which are based on clinical centers that provide Pompe disease treatment, revealed the prevalence rate of this disease to be 1 in every 350,914 persons.
Currently, AI-based methods are being designed to extract relevant information from unstructured medical data. This type of automated screening can be used for large-scale rare disease screening, which could increase the rate of diagnosing RDs in a cost-effective manner. Study findings A total of 104 patients were flagged by AI out of 350,116 patients who were admitted to any of the five Landeskliniken Salzburg clinic groups through the one-time application.
The AI-based automated screening method, including the review round with GPs and SPs, took less than one month to detect 21 suspected patients for every clinic. Therefore, this approach required 5.47 patients to be reviewed manually to identify one suspected patient.
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