Bone Fracture Detection using Artificial Intelligence - A Systematic Review

Bone prevalent medical problems remain fractures that require accurate and timely diagnosis to provide the best patient care. Bone fractures have long been detected via X-rays and CT scans, but artificial intelligence (AI) has ushered in a new era of diagnosis precision. This review article provides an in-depth review of current progress in AI-assisted fracture diagnosis, from its inception to recent advances. This article serves as a roadmap for the integration of artificial intelligence and orthopedic diagnostics, showing the way forward to improve patient outcomes and healthcare delivery through Incorporate artificial intelligence into bone fracture detection. The precision values found for Decision Trees, Naive Bayes, K Nearest Neighbors, Random Forests, and Support Vector Machine range from 0.64 to 0.92 for the various methods utilized in the study. According to statistics, this study's Support Vector Machine accuracy was higher than the majority of the papers which were analyzed