BONE FRACTURE DETECTION USING X RAY IMAGE

Effective patient care depends on early diagnosis of bone fractures and a decrease in diagnostic mistakes. This paper investigates how One sort of deep learning method called convolutional neural network networks (CNNs) can increase the speed as well as precision of bone fracture identification from X-ray pictures. in CNNs helping To differentiate between healthy and sick bones, the suggested method could help in the early identification of irregularities in the bones. To construct the ideal model, substantial potential in healthcare settings with an accuracy rate close to 90% and a sensitivity of 89.865% is required.Selective hyperparameters comprised of learning rates and epoch counts. The CNN framework displayed This superior performance level demonstrates the system’s ability to provide consistent and timely diagnostic support, reducing errors and improving patient outcomes.