Automating screening and diagnosis in the medical field saves time and reduces the
chances of misdiagnosis while saving on labor and cost for physicians. With the feasibility …

Background As big data and artificial intelligence (AI) in spine care, and medicine as a
whole, continue to be at the forefront of research, careful consideration to the quality and …

Background: Chronic back pain is a major health problem worldwide. Although its causes
can be diverse, biomechanical factors leading to spinal degeneration are considered a …

Background Recently, the Turing test has been used to investigate whether machines have
intelligence similar to humans. Our study aimed to assess the ability of an artificial …

Purpose To summarize and critically evaluate the existing studies for spinopelvic
measurements of sagittal balance that are based on deep learning (DL). Methods Three …

Purpose Artificial intelligence based on deep learning (DL) approaches enables the
automatic recognition of anatomic landmarks and subsequent estimation of various …

Purpose Since the critical shoulder angle (CSA) is considered a risk factor for shoulder
pathology and the intra-and inter-rater variabilities in its calculation are not negligible, we …

Objective This study aimed to develop and validate a deep learning (DL) algorithm for the
quantitative measurement of thoracolumbar (TL) fracture features, and to evaluate its …

ABSTRACT A robust definition of normal vertebral morphometry is required to confidently
identify abnormalities such as fractures. The Second National Health and Nutrition …

This study delves into the application of convolutional neural networks (CNNs) in evaluating
spinal sagittal alignment, introducing the innovative concept of incidence angles of inflection …