ML methods have shown promise in the identification and diagnosis of rare diseases. With the vast amounts of data now available through electronic health records and heterogeneous databases, AI algorithms can help quickly identify patterns and associations that would be difficult or impossible for human analysts to detect.
This review, published in the Biomedicines journal (by MDPI) aims to highlight the achievements of AI algorithms in the study of rare diseases in the past decade and advise researchers on which methods have proven to be most effective. The review will focus on specific rare diseases and will examine which AI methods have been most successful in their study.
The authors believe this review can guide clinicians and researchers in the successful application of Machine Learning in rare diseases.
