Evaluating DIAGEN-IA A Machine Learning Tool to Help Diagnose Pediatric Genetic Neurological Diseases

What this Trial Is About

Researchers are evaluating the DIAGEN-IA diagnostic support platform, designed to help identify pediatric neurological diseases with a genetic basis. The study aims to see if the platform reduces inappropriate referrals to clinical geneticists, improves the completeness of initial diagnostic evaluations, enhances referral quality, and increases user satisfaction. Conducted at Carlos Van Buren Hospital in Chile, the trial uses a prospective before-and-after design to compare outcomes between baseline and intervention phases. The study includes two 6-month phases. In the first phase, baseline data on referral appropriateness and evaluation completeness are collected without the platform. In the second phase, pediatric neurologists trained to use DIAGEN-IA will use the platform during consultations to guide referrals and recommend diagnostic tests. The platform uses a Bayesian network model integrating medical ontologies to suggest diagnoses and tests based on clinical data. Usage of the platform, including login frequency and evaluations performed, will be monitored. Participants include healthcare professionals providing care to children under 18 years old and responsible for referring suspected rare disease cases to clinical geneticists. The study collects demographic data and monitors referral appropriateness using a 5-point Likert scale, referral quality based on standard criteria, and user satisfaction via questionnaires at one and six months. Data will be anonymized, and the results aim to improve referral processes and diagnosis in pediatric neurological care.

Pediatric Neurogenetic Diagnosis Support Platform