Diseases such as retinitis pigmentosa or age-related macular degeneration each affect the eyesight of approximately 1 in 3,000 Americans. Unfortunately, the genetic causes underlying these conditions are varied and complex, making quick, accurate, and efficient diagnostics a challenging task for clinicians across the country. Researchers at the University of Michigan have developed systems and methods for integrating clinical data, along with patient-specific hereditary and demographic information to generate individualized lists of potential diagnoses, ranked likelihood. This information will guide clinicians in ordering further tests as they seek to establish a treatment plan for their patients. Integrating clinical and hereditary data Genetic diagnoses of retinal dystrophies can be complex – in some instances, nearly 200 different mutations can be linked to a single condition. Therefore, addition information is needed to arrive at an accurate, relevant clinical diagnosis. By incorporating family history, demographic information, objective test results, and clinical observation and comparing that information against a database of known symptoms and conditions, the disclosed technology uses a weighted algorithm to generate a ranked list of candidate genes for evaluation and potential diagnoses.
Applications • Diagnosis of inherited retinal diseases Advantages • Improved diagnosis accuracy • Quicker, more efficient results