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Use GPT-J Prompt Generation with RoBERTa for NER Models on Diagnosis Extraction of Periodontal Diagnosis from Electronic Dental Records
This study explored the usability of prompt generation on named entity recognition (NER) tasks and the performance in different settings of the prompt.
Extracting periodontitis diagnosis in clinical notes with RoBERTa and regular expression
This study aimed to utilize text processing and natural language processing (NLP) models to mine clinical notes for the diagnosis of periodontitis and to evaluate the performance of a named entity recognition (NER) model on different regular expression (RE) methods.
An End-to-end Entangled Segmentation and Classification Convolutional Neural Network for Periodontitis Stage Grading from Periapical Radiographic Images
We developed an end-to-end deep learning network HYNETS (Hybrid NETwork for pEriodoNTiTiS STagES from radiograpH) by integrating segmentation and classification tasks for grading periodontitis from periapical radiographic images.
Use of the Deep Learning Approach to Measure Alveolar Bone Level
Conclusion: The proposed DL model provides reliable RBL measurements and image-based periodontal diagnosis using periapical radiographic images.
