A5050939126- Spine and Intervertebral Disc Pathology
- Cervical and Thoracic Myelopathy
- Spinal Fractures and Fixation Techniques
- Musculoskeletal pain and rehabilitation
- Scoliosis diagnosis and treatment
- Medical Imaging and Analysis
- Spinal Cord Injury Research
- Spinal Hematomas and Complications
- Pelvic and Acetabular Injuries
- Management of metastatic bone disease
- Advanced Neuroimaging Techniques and Applications
- Spinal Dysraphism and Malformations
- Infectious Diseases and Tuberculosis
- Pain Mechanisms and Treatments
- Bone health and osteoporosis research
- Anesthesia and Pain Management
- Stroke Rehabilitation and Recovery
- Peripheral Nerve Disorders
- Spondyloarthritis Studies and Treatments
- Orthopaedic implants and arthroplasty
- Nerve Injury and Rehabilitation
- Parkinson's Disease and Spinal Disorders
- Nutrition and Health in Aging
- Radiomics and Machine Learning in Medical Imaging
- Nerve injury and regeneration
Chiba University
2016-2025
Research Organization of Information and Systems
2023-2025
Japan Agency for Medical Research and Development
2023
Teikyo University
2023
Kudanzaka Hospital
2021
University of Tsukuba
2021
Chiba University Hospital
2021
Shizuoka Cancer Center
2018-2020
Vanderbilt University Medical Center
2018-2020
Northwell Health
2019
(2020). Automated classification of hip fractures using deep convolutional neural networks with orthopedic surgeon-level accuracy: ensemble decision-making antero-posterior and lateral radiographs. Acta Orthopaedica: Vol. 91, No. 6, pp. 699-704.
Objective: In recent years, there has been an increase in research on the therapeutic effects of exergaming, but have few studies these types interventions for chronic low back pain. this study, we hypothesized that Nintendo Ring Fit Adventure (RFA) exergame would be effective patients with pain, and conducted a randomized prospective longitudinal study. Materials Methods: Patients pain were included Twenty randomly selected (9 males 11 females, mean age 49.3 years) RFA group, exergaming was...
Emergency medical triage is crucial for prioritizing patient care in emergency situations, yet its effectiveness can vary significantly based on the experience and training of personnel involved. This study aims to evaluate efficacy integrating Retrieval Augmented Generation (RAG) with Large Language Models (LLMs), specifically OpenAI's GPT models, standardize procedures reduce variability care.
Patients with multiple sclerosis present focal lesions throughout the spinal cord. There is a clinical need for non-invasive measurements of cord activity and functional organization in sclerosis, given cord's critical role disease. Recent reports spontaneous blood oxygenation level-dependent fluctuations using MRI suggest that, like brain, at rest organized into distinct, synchronized networks among grey matter regions, likely related to motor sensory systems. Previous studies looking...
Abstract The emergency department is an environment with a potential risk for diagnostic errors during trauma care, particularly fractures. Convolutional neural network (CNN) deep learning methods are now widely used in medicine because they improve accuracy, decrease misinterpretation, and efficiency. In this study, we investigated whether automatic localization classification using CNN could be applied to pelvic, rib, spine We also examined fracture detection algorithm help physicians...
Abstract To evaluate the radiological differences between diffuse idiopathic skeletal hyperostosis (DISH) and ankylosing spondylitis (AS) using whole spine computed tomography (CT), including sacroiliac joint (SIJ). The ossification bridging of spinal ligament fusion facet SIJ were evaluated in 111 patients who diagnosed with DISH 27 AS on CT. number anterior shape (candle-wax-type/ smooth-type) also evaluated. We further by matching their age sex. Complete was more common AS, whereas...
Study Design: Retrospective cohort study. Objective: To develop a machine learning (ML) model that predicts the progression of AIS using minimal radiographs and simple questionnaires during first visit. Summary Background Data: Several factors are associated with angle in patients AIS. However, it is challenging to predict angular at Methods: Among female treated single institution from July 2011 February 2023, 1119 cases were studied. Patient data, including demographic radiographic data...
Abstract Decline in mobility is a global issue that must be addressed rapidly aging societies. We aimed to clarify the association between locomotive syndrome (LS), condition of decreased and health literacy (HL) community-dwelling Japanese adults aged ≥ 40 years. A descriptive survey was conducted Onjuku Town, Japan, 2019 2023. The participants performed LS risk tests, including two-step test, stand-up tests 25-question geriatric function scale, assess mobility. They completed 14-item scale...
Abstract Purpose This study was designed to develop a machine learning (ML) model that predicts future Cobb angle in patients with adolescent idiopathic scoliosis (AIS) using minimal radiographs and simple questionnaires during the first second visits. Methods Our focused on 887 female AIS who were initially consulted at specialized center from July 2011 February 2023. Patient data, including demographic radiographic data based anterior-posterior lateral whole-spine radiographs, collected...
Study Design. Retrospective analysis of data collected across multiple centers. Objective. To develop machine learning models for predicting neurological outcomes one month postoperatively in patients with metastatic spinal tumors undergoing surgery, and to identify key factors influencing recovery. Summary Background Data. The increasing prevalence metastases has led a growing need surgical intervention address mechanical instability deficits. Predicting postoperative status, as assessed by...
Study Design. Retrospective analysis of magnetic resonance imaging (MRI). Objective. The aim this study was to evaluate the performance our convolutional neural network (CNN) in differentiating between spinal schwannoma and meningioma on MRI. We compared CNN that two expert radiologists. Summary Background Data. Preoperative discrimination schwannomas meningiomas is crucial because different surgical procedures are required for their treatment. A deep-learning approach based CNNs gaining...