ARTIFICIAL INTELLIGENCE IMPROVES THE ACCURACY OF RESIDENTS IN THE DIAGNOSIS OF HIP FRACTURES: A MULTICENTER STUDY

Artificial intelligence improves the accuracy of residents in the diagnosis of hip fractures: a multicenter study

Abstract Background Less experienced clinicians sometimes make misdiagnosis of hip fractures.We developed computer-aided diagnosis (CAD) system for hip fractures on plain X-rays using a deep learning model trained on a large dataset.In this study, we examined whether the accuracy of the diagnosis of hip fracture of the residents could be improved b

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Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs

Short-term load forecasting is crucial for the operations planning of an electrical grid.Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources.The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural network

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Long Term Evaluation of the Barrier Properties of Polymer/Metal Oxide Hybrid Layers for Use in Medical Implants

Encapsulation is essential for mechanically flexible and electrically active implants as it protects them Stick from the harsh environment inside the body.Since the performance and longevity of implants depends on the quality of encapsulation, research continues into new and better encapsulation strategies.Chemical vapour deposition can be used to

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Giant gastric lipoma mimicking well-differentiated liposarcoma

Authors report the case of a 51-year-old man, presenting with epigastralgia of recent onset.Physical exam was unremarkable.Endoscopy revealed a large, ulcerated, submucosal, antral tumor.CT scan reveals an antral mass with fat attenuation.The patient underwent Artificial plant a total gastrectomy.Macroscopic examination identified in the antral wal

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