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Found 6 papers, 2 papers with code
Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models
Using this dataset, we evaluate the performance of seven LLMs applied zero-shot for the task of conditionally extracting numerical findings from trial reports.
Keeping Users Engaged During Repeated Administration of the Same Questionnaire: Using Large Language Models to Reliably Diversify Questions
Psychometric testing revealed consistent covariation between the external criterion and the focal measure administered across the three conditions, demonstrating the reliability and validity of the LLM-generated variants.
Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews
We conducted 16 interviews with international systematic review experts to characterize the perceived utility and risks of LLMs in the specific context of medical evidence reviews.
Metal Artifact Reduction with Intra-Oral Scan Data for 3D Low Dose Maxillofacial CBCT Modeling
To improve the learning ability, the proposed network is designed to take advantage of the intra-oral scan data as side-inputs and perform multi-task learning of auxiliary tooth segmentation.
Fully automatic integration of dental CBCT images and full-arch intraoral impressions with stitching error correction via individual tooth segmentation and identification
The proposed method is intended not only to compensate the low-quality of CBCT-derived tooth surfaces with IOS, but also to correct the cumulative stitching errors of IOS across the entire dental arch.
Automated 3D cephalometric landmark identification using computerized tomography
This paper presents a semi-supervised DL method for 3D landmarking that takes advantage of anonymized landmark dataset with paired CT data being removed.
