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Year : 2021  |  Volume : 5  |  Issue : 1  |  Page : 4-9

Artificial intelligence application in bone fracture detection

Division of Orthopedic, Department of Surgery, Sultan Qaboos University Hospital, Muscat, Oman

Correspondence Address:
Dr. Ahmed AlGhaithi
P. O. Box 478 P.C 130, Muscat
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jmsr.jmsr_132_20

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The interest of researchers, clinicians, and industry in artificial intelligence (AI) continues to grow, especially with recent deep-learning (DL) advances. Recent published reports have shown the utility of DL for bone fracture diagnosis in the radiological examination. It is important for practicing physicians to recognize the current scope of DL as it may impact the clinical practices in the near future. This article will give an insight to the practicing clinician of the current advances in AI fracture diagnosis by reviewing the current literature on this participant. Electronic databases were searched for relevant articles relating to AI applications in bone fracture detection. We included all published work in PubMed, Medline, and Cross-references, which satisfied the inclusion criteria. The search identified 104 references. Of those, 13 articles were eligible for the analysis. AI advancements in fracture imaging applications can be divided into the categories of fracture detection, classification, segmentation, and noninterpretive tasks. Despite the potential work presented in the literature, there are many challenges in the form of clinical translation and its widespread uses. These challenges range from the proof of safety to clearance from the regulatory agencies.

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