AIMC Topic: Scoliosis

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Evaluating the readability and quality of AI-generated scoliosis education materials: a comparative analysis of five language models.

Scientific reports
The complexity of scoliosis-related terminology and treatment options often hinders patients and caregivers from understanding their choices, making it difficult to make informed decisions. As a result, many patients seek guidance from artificial int...

Development and validation of a keypoint region-based convolutional neural network to automate thoracic Cobb angle measurements using whole-spine standing radiographs.

Acta neurochirurgica
PURPOSE: Adolescent idiopathic scoliosis (AIS) affects a significant portion of the adolescent population, leading to severe spinal deformities if untreated. Diagnosis, surgical planning, and assessment of outcomes are determined primarily by the Cob...

Patient education strategies in pediatric orthopaedics: using ChatGPT to answer frequently asked questions on scoliosis.

Spine deformity
PURPOSE: Patients increasingly rely on online resources to better understand their health conditions. ChatGPT could satisfy the demand for reliable and accessible online health education resources, yet few studies have applied this to pediatric ortho...

Three-dimensional markerless surface topography approach with convolutional neural networks for adolescent idiopathic scoliosis screening.

Scientific reports
Adolescent idiopathic scoliosis (AIS) is a three-dimensional lateral and torsional deformity of the spine, affecting up to 5% of the population. Traditional scoliosis screening methods exhibit limited accuracy, leading to unnecessary referrals and ex...

SSAT-Swin: Deep Learning-Based Spinal Ultrasound Feature Segmentation for Scoliosis Using Self-Supervised Swin Transformer.

Ultrasound in medicine & biology
OBJECTIVE: Scoliosis, a 3-D spinal deformity, requires early detection and intervention. Ultrasound curve angle (UCA) measurement using ultrasound images has emerged as a promising diagnostic tool. However, calculating the UCA directly from ultrasoun...

A deep learning model for radiological measurement of adolescent idiopathic scoliosis using biplanar radiographs.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate measurement of the spinal alignment parameters is crucial for diagnosing and evaluating adolescent idiopathic scoliosis (AIS). Manual measurement is subjective and time-consuming. The recently developed artificial intelligence mo...

Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network.

Journal of orthopaedic surgery and research
BACKGROUND: Traditional diagnostic tools for scoliosis screening necessitate a substantial number of specialized personnel and equipment, leading to inconvenience that can result in missed opportunities for early diagnosis and optimal treatment. We h...

Automated measurement of pelvic parameters using convolutional neural network in complex spinal deformities: overcoming challenges in coronal deformity cases.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Accurate and consistent measurement of sagittal alignment is challenging, particularly in patients with severe coronal deformities, including degenerative lumbar scoliosis (DLS).

Adjacent point aided vertebral landmark detection and Cobb angle measurement for automated AIS diagnosis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Adolescent Idiopathic Scoliosis (AIS) is a prevalent structural deformity disease of human spine, and accurate assessment of spinal anatomical parameters is essential for clinical diagnosis and treatment planning. In recent years, significant progres...