Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/6363
Title: The Development of Artificial Intelligence in Knee Joint MRI Detection
Authors: Chen Xu 
Ismail, Nor Alina 
Gan Hong Seng 
Keywords: Artificial intelligence;Knee Joint;Application
Issue Date: 1-Jun-2024
Publisher: Asian Scholars Network
Journal: International Journal of Business and Technology Management 
Abstract: 
The application of artificial intelligence in the diagnosis and analysis of knee joint MRI has significantly advanced, leveraging technologies like machine learning and deep learning to enhance both accuracy and efficiency. AI models are adept at identifying, classifying, and predicting various pathologies such as osteoarthritis and ligament tears by analyzing complex imaging data. This facilitates more accurate diagnoses by assisting radiologists. Key developments include automation of image segmentation, image resolution enhancement, and noise reduction in MRI scans. Despite these advances, integrating AI into clinical workflows, managing data variability, and ensuring extensive validation pose ongoing challenges. Nonetheless, AI's potential to transform diagnostic processes, improve patient outcomes, and reduce healthcare costs by streamlining workflows remains promising
Description: 
Mycite
URI: http://hdl.handle.net/123456789/6363
ISSN: 2682-7646
DOI: https://doi.org/10.55057/ijbtm.2024.6.2.21
Appears in Collections:Journal Indexed MyCite - FSDK

Files in This Item:
File Description SizeFormat
View of The Development of Artificial Intelligence in Knee Joint MRI Detection.pdf1.92 MBAdobe PDFView/Open
Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.