Prediction of functional prognosis of orthopedic diseases using AI (Radiomics)

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K18052
• Research Category: Grant-in-Aid for Early-Career Scientists
• Allocation Type: Multi-year Fund
• Review Section: Basic Section 56020:Orthopedics-related
• Research Institution: Chiba University
• Principal Investigator: Maki Satoshi 千葉大学, 医学部附属病院, 助教 (00771982)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 人工知能 / 脊髄損傷 / 頚椎症性脊髄症 / 大腿骨近位部骨折 / 転移性脊椎腫瘍

Outline of Final Research Achievements

Using MRI images, it has been found that the severity of paralysis in spinal cord injury patients can be predicted with 88% accuracy after one month, demonstrating the effectiveness of AI in this area. It has also been successful in predicting surgical outcomes for patients with cervical ossification of the posterior longitudinal ligament using machine learning based on patient information prior to surgery. Furthermore, by evaluating the ability of AI to detect femoral fractures using hip X-ray images, it has been found that there is potential to improve the accuracy of diagnosis. In addition, AI has been shown to be useful in identifying whether fractures are due to cancerous spinal metastasis or osteoporosis using MRI images. As a result, physicians can better understand diseases and patient care is expected to improve.

Free Research Field

整形外科学

Academic Significance and Societal Importance of the Research Achievements

この研究は、医療の現場でAI技術を活用して、より正確な診断や治療法の選択を可能にすることで、患者のケアが向上することが期待される。また、医療従事者の負担を軽減し、効率的な医療サービスの提供に貢献することができる可能性がある。この研究は、医療の現場でAI技術を活用して、より正確な診断や治療法の選択を可能にすることで、患者のケアが向上することが期待されている。また、医療従事者の負担を軽減し、効率的な医療サービスの提供に貢献する可能性がある。