Evaluating Classification Consistency of Oral Lesion Images for Use in an Image Classification Teaching Tool

• Главные авторы: Yuxin Shen (Автор), Minn N. Yoon (Автор), Silvia Ortiz (Автор), Reid Friesen (Автор), Hollis Lai (Автор)
• Формат: ‌
• Опубликовано: MDPI AG, 2021-08-01T00:00:00Z.
• Предметы: article
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A web-based image classification tool (DiLearn) was developed to facilitate active learning in the oral health profession. Students engage with oral lesion images using swipe gestures to classify each image into pre-determined categories (e.g., left for refer and right for no intervention). To assem...