A5030892111- Oral microbiology and periodontitis research
- Colorectal Cancer Screening and Detection
- Dental Health and Care Utilization
- Kidney Stones and Urolithiasis Treatments
- Recommender Systems and Techniques
- Dental Radiography and Imaging
- Paleopathology and ancient diseases
Yonsei University
2019-2022
Recommendation systems are tasked with the complex challenge of modeling high-dimensional interactions between users and items to deliver personalized recommendations. This paper introduces Cyclic Dual Latent Discovery (CDLD), a novel method that employs dual deep neural networks (DNNs) in cyclic training process discover latent traits based on their interactions. CDLD operates principle inherently possess information about traits. By cyclically refining these through two interconnected...
Purpose: Convolutional neural networks (CNNs) have been studied for detecting bone metastases on scans; however, the application of ConvNeXt and transformer models has not yet explored. This study aims to evaluate performance various deep learning models, including in diagnosing metastatic lesions from scans. Materials Methods: We retrospectively analyzed scans patients with cancer obtained at 2 institutions: training validation sets (n=4626) were Hospital 1 test set (n=1428) was 2. The...
This study aimed to predict the composition of urolithiasis using deep learning from urinary stone images.We classified 1,332 stones into 31 classes according composition. The top 4 with a frequency 110 or more (class 1: calcium oxalate monohydrate [COM] 100%, class 2: COM 80%+struvite 20%, 3: 60%+calcium dihydrate [COD] 40%, 4: uric acid 100%) were selected. With 965 images classes, we used seven convolutional neural networks (CNN) classify and compared their classification...
Objectives The primary objective of this study was to determine if the number missing teeth could be predicted by oral disease pathogens, and secondary assess whether deep learning is a better way predicting than multivariable linear regression (MLR). Methods Data were collected through review patient's initial medical records. A total 960 participants cross-sectionally surveyed. MLR analysis performed relationship between results real-time PCR assay (done for quantification 11 pathogens)....