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[Artificial intelligence for the comprehensive approach to orphan/rare diseases: A scoping review]
L M Acero Ruge1, D A Vásquez Lesmes1, E H Hernández Rincón2
1Medicina Familiar y Comunitaria, Universidad de La Sabana, Facultad de Medicina, Chía, Colombia.
Introduction:
Orphan diseases (OD) are rare but collectively common, presenting challenges such as late diagnoses, disease progression, and limited therapeutic options. Recently, artificial intelligence (AI) has gained interest in the research of these diseases.
Objective:
To synthesize the available evidence on the use of AI in the comprehensive approach to orphan diseases.
Methods:
An exploratory systematic review of the Scoping Review type was conducted in PubMed, Bireme, and Scopus from 2019 to 2024.
Results:
fifty-six articles were identified, with 21.4% being experimental studies; 28 documents did not specify an OD, 8 documents focused primarily on genetic diseases; 53.57% focused on diagnosis, and 36 different algorithms were identified.
Conclusions:
The information found shows the development of AI algorithms in different clinical settings, confirming the potential benefits in diagnosis times, therapeutic options, and greater awareness among health professionals.
Insights
Artificial intelligence (AI) shows promise in addressing challenges in rare orphan diseases (OD). AI algorithms are advancing diagnosis, therapeutic options, and awareness for these collectively common conditions.
Area of Science:
- Medical Informatics
- Computational Biology
- Rare Diseases Research
Background:
- Orphan diseases (OD) are rare individually but collectively common, posing significant diagnostic and therapeutic challenges.
- Limited treatment options and delayed diagnoses contribute to disease progression in OD patients.
- Artificial intelligence (AI) is emerging as a valuable tool for advancing OD research and patient care.
Approach:
- An exploratory systematic review of the scoping review type was performed.
- Literature searches were conducted in PubMed, Bireme, and Scopus databases.
- The review covered publications from 2019 to 2024.
Key Points:
- Fifty-six articles were identified, with 21.4% being experimental studies.
- A significant portion of studies (53.57%) focused on diagnosis, with 36 different AI algorithms identified.
- Many documents did not specify an OD, while 8 focused on genetic diseases.
Conclusions:
- AI algorithms are being developed for diverse clinical applications in orphan diseases.
- AI demonstrates potential to reduce diagnosis times and improve therapeutic strategies for OD.
- Increased awareness and application of AI can benefit health professionals managing rare diseases.
