Mohammed Aslam Khan -, Mohd. Yaseen Ahmed -, Syed Safadar Hussain -, Khutaija Abid -
{"title":"Machine Learning for the Identification of Bone Deformities","authors":"Mohammed Aslam Khan -, Mohd. Yaseen Ahmed -, Syed Safadar Hussain -, Khutaija Abid -","doi":"10.37082/ijirmps.v11.i1.230311","DOIUrl":null,"url":null,"abstract":"The success of machine learning algorithms in medical imaging has boosted the demand for models that have been artificially trained to function more rapidly and effectively in the medical profession. In this paper, a method for identifying bone fractures using machine learning algorithms is presented, which can help to lighten the workload of orthopedics. Instead of spending hours in radiology departments, the substantial application of machine learning in this era of huge medical data will make it possible to obtain information from the available X-ray images. The imaging techniques described in this study can quickly determine whether a bone fracture has occurred in a human body after an X-ray has been obtained.","PeriodicalId":246139,"journal":{"name":"International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences","volume":"50 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37082/ijirmps.v11.i1.230311","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The success of machine learning algorithms in medical imaging has boosted the demand for models that have been artificially trained to function more rapidly and effectively in the medical profession. In this paper, a method for identifying bone fractures using machine learning algorithms is presented, which can help to lighten the workload of orthopedics. Instead of spending hours in radiology departments, the substantial application of machine learning in this era of huge medical data will make it possible to obtain information from the available X-ray images. The imaging techniques described in this study can quickly determine whether a bone fracture has occurred in a human body after an X-ray has been obtained.