Publications by authors named "Loon Ying Tan"
Article Synopsis
- A deep learning model was developed to detect and classify cervical cord signal abnormalities, spinal canal, and neural foraminal stenosis on MRI, aimed at improving reporting efficiency and consistency for cervical spondylosis.
- The study analyzed 504 cervical spine MRIs from a patient sample with a mean age of 58, using 90% for training and 10% for internal testing, with additional external testing on another 100 MRIs.
- Results showed the DL model achieved substantial agreement with human readers, outperforming them in classifying spinal canal and foraminal stenosis, and exhibited a high recall of 92.3% for cord signal abnormalities, demonstrating its potential effectiveness in clinical practice.
Objective: To evaluate the impact of pre-operative contrast-enhanced mammography (CEM) in breast cancer patients with dense breasts.
Methods: We conducted a retrospective review of 232 histologically proven breast cancers in 200 women (mean age: 53.4 years ± 10.