Medical Expert Knowledge Meets AI to Enhance Symptom Checker Performance for Rare Disease Identification in Fabry Disease: Mixed Methods Study.

Anne Pankow^1,2, Nico Meißner-Bendzko³, Jessica Kaufeld⁴, Laura Fouquette³, Fabienne Cotte³, Stephen Gilbert⁵, Ewelina Türk³, Anibh Das⁶, Christoph Terkamp², Gerhard-Rüdiger Burmester¹, Annette Doris Wagner⁴

¹Department of Rheumatology and Clinical Immunology, Charité-Universitätsmedizin Berlin, Berlin, Germany.

²Department of Gastroneterology, Hepatology, Infectious Diseases and Endocrinology, Hannover Medical School, Hannover, Germany.

³Ada Health GmbH, Berlin, Germany.

⁴Department of Nephrology and Hypertension, Hannover Medical School, Carl-Neuberg-Strasse 1, Hannover, 30625, Germany, 49 511 532 3745.

⁵Else Kröner Fresenius Center for Digital Health, TU Dresden University of Technology, Dresden, Germany.

⁶Department of Paediatrics, Hannover Medical School, Hannover, Germany.

PubMed PMC DOI PDF

Abstract

BACKGROUND: Rare diseases, which affect millions of people worldwide, pose a major challenge, as it often takes years before an accurate diagnosis can be made. This delay results in substantial burdens for patients and health care systems, as misdiagnoses lead to inadequate treatment and increased costs. Artificial intelligence (AI)-powered symptom checkers (SCs) present an opportunity to flag rar…

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