Abstract
As life expectancy and the proportion of the population over the age of 65 increases, osteoporosis and its clinical consequence, fragility fractures, has become a growing issue in both medical and economic terms. With the objective of facilitating early diagnosis and forecasting the outcomes of osteoporosis and its repercussions, the global scientific community has initiated efforts to develop artificial intelligence (AI)-based solutions. Specifically, artificial intelligence (AI) models that use either supervised or unsupervised learning have particularly compelling applications in screening for osteoporosis and fragility fractures, evaluating fracture risk, assessing response to treatment, and data analysis in applied research. However, the capabilities of this technology as an augment to medical practice should not be overestimated, as it has not been able to outperform conventional approaches for fracture prediction. Better model design is required to ensure appropriate application and validation of AI in the treatment of osteoporosis.
| Original language | English (US) |
|---|---|
| Title of host publication | Artificial Intelligence in Orthopaedic Surgery Made Easy |
| Publisher | Springer Nature |
| Pages | 189-195 |
| Number of pages | 7 |
| ISBN (Electronic) | 9783031703102 |
| ISBN (Print) | 9783031703096 |
| DOIs | |
| State | Published - Jan 1 2024 |
| Externally published | Yes |
Keywords
- Bone mineral density
- Dual X-ray absorptiometry
- Fragility fractures
- FRAX
- Osteoporosis
ASJC Scopus subject areas
- General Computer Science
- General Medicine
- General Biochemistry, Genetics and Molecular Biology
- General Engineering
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