Emerging machine learning (ML) technologies have the potential to significantly improve the research and treatment of rare diseases, which constitute a vast set of diseases that affect a small proportion of the total population. Artificial Intelligence (AI) algorithms can help to quickly identify patterns and associations that would be difficult or impossible for human analysts to detect. Predictive modeling techniques, such as deep learning, have been used to forecast the progression of rare diseases, enabling the development of more targeted treatments. Moreover, AI has also shown promise in the field of drug development for rare diseases with the identification of subpopulations of patients who may be most likely to respond to a particular drug. This review 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, as defined by a prevalence rate that does not exceed 1–9/100,000 on Orphanet, and will examine which AI methods have been most successful in their study. We believe this review can guide clinicians and researchers in the successful application of ML in rare diseases.
The Impact of Artificial Intelligence in the Odyssey of Rare Diseases
Anna Visibelli,Bianca Roncaglia,O. Spiga,Annalisa Santucci
Published 2023 in Biomedicines
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- Publication year
2023
- Venue
Biomedicines
- Publication date
2023-03-01
- Fields of study
Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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