AI and Data Ethics in Endodontic Research

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This guide explores the vital role and ethics in data handling for AI, emphasizing informed consent and data security. It covers cohort and data curation, ensuring diverse representation and quality improvement. Additionally, it discusses standards and annotation tools like ITK-SNAP and Labelbox for accurate data labeling. Preprocessing techniques such as image resizing and normalization, along with evaluation metrics like IoU, Dice, Sensitivity, and AUC, are detailed. Finally, it highlights...