Improving TMJ Diagnosis: A Deep Learning Approach for Detecting Mandibular Condyle Bone Changes by Kader Azlağ Pekince, Adem Pekince, Buse Yaren Kazangirler

“…The aim of this study is to enable the detection and diagnosis of mandibular condyle degenerations, which are difficult to observe and diagnose on panoramic radiographs, using deep learning methods. <b>Methods</b>: A total of 3875 condylar images were obtained from panoramic radiographs. …”
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COMPARISON OF DATASET OVERSAMPLING ALGORITHMS AND THEIR APPLICABILITY TO THE CATEGORIZATION PROBLEM by Denys Teslenko, Anna Sorokina, Artem Khovrat, Nural Huliiev, Valentyna Kyriy

“…The article solves the following tasks: to analyze approaches to solving the problem – preprocessing methods, learning methods, hybrid methods and algorithmic approaches; to define and describe the oversampling algorithms most often used to balance datasets; to select classification algorithms that will serve as a tool for establishing the quality of balancing by checking the applicability of the datasets obtained after oversampling; to determine metrics for assessing the quality of classification for comparison; to conduct experiments according to the proposed methodology. …”
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Diagnostic Models for Differentiating COVID-19-Related Acute Ischemic Stroke Using Machine Learning Methods by Eylem Gul Ates, Gokcen Coban, Jale Karakaya

“…This study aims to evaluate the impact of COVID-19 on acute ischemic stroke (AIS) using radiomic features extracted from brain MR images and machine learning methods. <b>Methods:</b> This retrospective study included MRI data from 57 patients diagnosed with AIS who presented to the Department of Radiology at Hacettepe University Hospital between March 2020 and September 2021. …”
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