首页|University of Malaya Reports Findings in Machine Learning (Automated transtibial prosthesis alignment: A systematic review)
University of Malaya Reports Findings in Machine Learning (Automated transtibial prosthesis alignment: A systematic review)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news originating from Kuala Lumpur, Malaysia , by NewsRx correspondents, research stated, “This comprehensive systematic revi ew critically analyzes the current progress and challenges in automating transti bial prosthesis alignment. The manual identification of alignment changes in pro stheses has been found to lack reliability, necessitating the development of aut omated processes.” Our news journalists obtained a quote from the research from the University of M alaya, “Through a rigorous systematic search across major electronic databases, this review includes the highly relevant studies out of an initial pool of 2111 records. The findings highlight the urgent need for automated alignment systems in individuals with transtibial amputation. The selected studies represent cutti ng-edge research, employing diverse approaches such as advanced machine learning algorithms and innovative alignment tools, to automate the detection and adjust ment of prosthesis alignment. Collectively, this review emphasizes the immense p otential of automated transtibial prosthesis alignment systems to enhance alignm ent accuracy and significantly reduce human error. Furthermore, it identifies im portant limitations in the reviewed studies, serving as a catalyst for future re search to address these gaps and explore alternative machine learning algorithms .”
Kuala LumpurMalaysiaAsiaCyborgsE merging TechnologiesHealth and MedicineMachine LearningMedical DevicesPr osthetics
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