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Can a decision support system accelerate rare disease diagnosis? Evaluating the potential impact of Ada DX in a retrospective study.

Simon RonickeMartin C HirschEwelina TürkKatharina LarionovDaphne TientcheuAnnette D Wagner
Published in: Orphanet journal of rare diseases (2019)
Ada DX provided accurate rare disease suggestions in most rare disease cases. In many cases, Ada DX provided correct rare disease suggestions early in the course of the disease, sometimes at the very beginning of a patient journey. The interpretation of these results indicates that Ada DX has the potential to suggest rare diseases to physicians early in the course of a case. Limitations of this study derive from its retrospective and unblinded design, data input by a single user, and the optimization of the knowledge base during the course of the study. Results pertaining to the system's accuracy should be interpreted cautiously. Whether the use of Ada DX reduces the time to diagnosis in rare diseases in a clinical setting should be validated in prospective studies.
Keyphrases
  • healthcare
  • primary care
  • machine learning
  • high resolution
  • risk assessment
  • cross sectional
  • deep learning
  • climate change