Objectives To compare the performance of radiologists in characterizing and diagnosing
pulmonary nodules/masses with and without deep learning (DL)–based computer-aided …

This paper is concerned with configurations of two-material thermal conductors that minimize
the Dirichlet energy for steady-state diffusion equations with nonlinear boundary conditions …

We proposed a bimodal artificial intelligence that integrates patient information with images
to diagnose spinal cord tumors. Our model combines TabNet, a state-of-the-art deep …

Purpose To assess whether transfer learning with a bidirectional encoder representations
from transformers (BERT) model, pretrained on a clinical corpus, can perform sentence-level …

In this study, we present a self-supervised learning (SSL)-based model that enables
anatomical structure-based unsupervised anomaly detection (UAD). The model employs an …

Background Health-related patient-reported outcomes (HR-PROs) are crucial for assessing
the quality of life among individuals experiencing low back pain. However, manual data …

Cervical sagittal alignment is an essential parameter for the evaluation of spine disorders.
Manual measurement is time-consuming and burdensome to measurers. Artificial intelligence (…

Background The Japanese Orthopaedic Association National Registry (JOANR) was
recently launched in Japan and is expected to improve the quality of medical care. However, …

In this article, a new type of comparison theorem for some second-order nonlinear parabolic
systems with nonlinear boundary conditions is given, which can cover classical linear …

Fluorine-18-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography (PET)/computed
tomography (CT) is widely used for the detection, diagnosis, and clinical decision-making in …