Copyright: ©Author(s) 2026.
World J Orthop. Apr 18, 2026; 17(4): 113710
Published online Apr 18, 2026. doi: 10.5312/wjo.v17.i4.113710
Published online Apr 18, 2026. doi: 10.5312/wjo.v17.i4.113710
Table 1 Reasons for false positives and false negatives, n (%)
| Category | False positives | False negatives | Total errors |
| Old/healed fracture/variant | 4 (6.9) | 3 (5.6) | 7 (6.2) |
| Subtle/minimally displaced fracture | 1 (1.7) | 50 (92.6) | 51 (45.5) |
| Overlapping and projection artifact | 0 (0.0) | 1 (1.9) | 1 (0.9) |
| Growth plate/degenerative changes/prosthesis | 53 (91.4) | 0 (0.0) | 53 (47.3) |
| Total | 58 (100) | 54 (100) | 112 (100) |
- Citation: Al Hajaj SW, Soliman K, Zafar M, Garnham C, Al Hajaj D, Elshafie O, Alsswah A, Elwan MH. From subtle breaks to missed diagnoses: Real-world evaluation of an artificial intelligence fracture detection tool. World J Orthop 2026; 17(4): 113710
- URL: https://www.wjgnet.com/2218-5836/full/v17/i4/113710.htm
- DOI: https://dx.doi.org/10.5312/wjo.v17.i4.113710