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Bones play a significant role in human body support, allowing us to use our muscles to walk, ride a bike, and hold a child. A bone fracture is a medical condition that occurs when a bone is cracked or broken due to an accident or trauma. Fractures can range in severity from a small crack in the bone to a complete break, where the bone is broken into two or more pieces. Accidents are one of the most common causes of bone fractures, and they can occur in a variety of ways, such as falls, sports injuries, car accidents, and workplace accidents. The severity of the fracture depends on the amount of force applied to the bone, the location of the fracture, and the age and health of the person. To deal with this problem, it requires an essential need of prediction system for the detection of bone fractures in the human body. The artificial intelligence subfield of machine learning offers distinguished assistance in event prediction and trains its models using data from real-world occurrences. In this chapter, ML and DL algorithms for predicting bone fractures using support vector machine, decision tree, random forest, and convolutional neural network (CNN) algorithms are discussed. Out of these, SVM outperformed with 86% accuracy.

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Bone Fracture Prediction Using Machine Learning and Deep Learning Techniques

  • 会议论文

  • 发表日期：

    2025年

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  • Satya Vamsi Kumar Appala,
  • S. V. V. D. Jagadeesh,
  • M. Durga Satish,
  • B. Sridevi

摘要

Bones play a significant role in human body support, allowing us to use our muscles to walk, ride a bike, and hold a child. A bone fracture is a medical condition that occurs when a bone is cracked or broken due to an accident or trauma. Fractures can range in severity from a small crack in the bone to a complete break, where the bone is broken into two or more pieces. Accidents are one of the most common causes of bone fractures, and they can occur in a variety of ways, such as falls, sports injuries, car accidents, and workplace accidents. The severity of the fracture depends on the amount of force applied to the bone, the location of the fracture, and the age and health of the person. To deal with this problem, it requires an essential need of prediction system for the detection of bone fractures in the human body. The artificial intelligence subfield of machine learning offers distinguished assistance in event prediction and trains its models using data from real-world occurrences. In this chapter, ML and DL algorithms for predicting bone fractures using support vector machine, decision tree, random forest, and convolutional neural network (CNN) algorithms are discussed. Out of these, SVM outperformed with 86% accuracy.