Machine learning and deep neural network-based learning in osteoarthritis knee

作     者：Harish V K Ratna Madhan Jeyaraman Naveen Jeyaraman Arulkumar Nallakumarasamy Shilpa Sharma Manish Khanna Ashim Gupta 

作者机构：Department of OrthopaedicsRathimed Speciality HospitalChennai 600040Tamil NaduIndia Department of OrthopaedicsACS Medical College and HospitalDr MGR Educational and Research InstituteChennai 600077Tamil NaduIndia Department of OrthopaedicsSouth Texas Orthopaedic Research InstituteLaredoTX 78045United States Department of Paediatric SurgeryAll India Institute of Medical SciencesNew Delhi 110029India Department of OrthopaedicsAutonomous State Medical CollegeAyodhya 224133Uttar PradeshIndia Department of Regenerative MedicineRegenerative OrthopaedicsNoida 201301Uttar PradeshIndia Department of Regenerative MedicineFuture BiologicsLawrencevilleGA 30043United States Department of Regenerative MedicineBioIntegarteLawrencevilleGA 30043United States 

出 版 物：《World Journal of Methodology》 (世界方法学杂志)

年 卷 期：2023年第13卷第5期

页      面：419-425页

学科分类：1002[医学-临床医学] 100210[医学-外科学(含：普外、骨外、泌尿外、胸心外、神外、整形、烧伤、野战外)] 10[医学] 

主　　题：Osteoarthritis Knee Artificial intelligence Machine learning Deep neural network 

摘      要：Osteoarthritis(OA)of the knee joint is considered the commonest musculoskeletal condition leading to marked disability for patients residing in various regions around the *** of machine learning(ML)in doing research regarding OA has brought about various clinical advances viz,OA being diagnosed at preliminary stages,prediction of chances of development of OA among the population,discovering various phenotypes of OA,calculating the severity in OA structure and also discovering people with slow and fast progression of disease pathology,*** publications are available regarding machine learning methods for the early detection of *** key features are detected by morphology,molecular architecture,and electrical and mechanical *** addition,this particular technique was utilized to assess non-interfering,non-ionizing,and in-vivo techniques using magnetic resonance *** is being utilized in OA,chiefly with the formulation of large cohorts viz,the OA Initiative,a cohort observational study,the Multicentre Osteoarthritis Study,an observational,prospective longitudinal study and the Cohort Hip&Cohort Knee,an observational cohort prospective study of both hip and knee *** ML has various contributions and enhancing applications,it remains an imminent field with high potential,also with its *** more studies are to be carried out to find more about the link between machine learning and knee osteoarthritis,which would help in the improvement of making decisions clinically,and expedite the necessary interventions.