Year: 2023
Type: article
Abstract: earch for dental research, Dental CLAIRES, utilizes periapical radiographs and associated clinical details such as periodontal diagnosis, demographic information to retrieve the best-matched images based on the text query. We applied a contrastive representation learning method to find images described by the user's text by maximizing the similarity score of positive pairs (true pairs) and minimizing the score of negative pairs (random pairs). Our model achieved a hit@3 ratio of 96% and a Mean Reciprocal Rank (MRR) of 0.82. We also designed a graphical user interface that allows researchers to verify the model's performance with interactions.
Source: PubMed Central
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: Recruitment of Rising Stars, Open Health Natural Language Processing Collaboratory, Finding combinatorial drug repositioning therapy for Alzheimer's disease and related dementias, G5388406022, Collaborative Research: SaTC: CORE: Medium: PREMED: Privacy-Preserving and Robust Computational Phenotyping using Multisite EHR Data, G6646588417, Biomedical Informatics, Genomics, and Translational Cancer Research Training Program (BIG-TCR), G8770013317
OpenAlex ID: W4381716067