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Predicting the Risk of Total Hip Replacement by Using A Deep Learning Algorithm on Plain Pelvic Radiographs: Diagnostic Study

Predicting the Risk of Total Hip Replacement by Using A Deep Learning Algorithm on Plain Pelvic Radiographs: Diagnostic Study

For nonsquare input radiographs, the image was padded to achieve a square size, with zero values added to the width or height to ensure that the convolution operation preserves the aspect ratio of the hip and pelvis shape in the radiograph. The detailed framework of the development method has been described in Multimedia Appendix 1 and a previous study [39]. The hip ROIs were then inputted into a further network for classification.

Chih-Chi Chen, Cheng-Ta Wu, Carl P C Chen, Chia-Ying Chung, Shann-Ching Chen, Mel S Lee, Chi-Tung Cheng, Chien-Hung Liao

JMIR Form Res 2023;7:e42788

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Diagnostic Accuracy and Confidence in Management of Forearm and Hand Fractures Among Foundation Doctors in the Accident and Emergency Department: Survey Study

Diagnostic Accuracy and Confidence in Management of Forearm and Hand Fractures Among Foundation Doctors in the Accident and Emergency Department: Survey Study

Non–clinician-related factors have been shown to influence accurate radiograph interpretation, including time of day and location of fracture [5,6]. Junior doctors tend to have lower accuracy compared to more experienced clinicians and radiologists and lower confidence in their diagnoses. This has been attributed in part to the limited teaching on radiograph interpretation at medical schools [7].

Ben Gompels, Tobin Rusby, Richard Limb, Peter Ralte

JMIR Form Res 2023;7:e45820

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