Nanomaterials in Machine Learning Based Prosthesis
Deepali Salwan and Shri Kant
Machine learning has found its application in various fields. With the advent of technology, it has even found its way in the prosthesis field as doctors are using nano materials to conduct surgery in amputees and predicting the results of the surgery with the help of machine learning. The same techniques have also been successfully applied within the medical field, in addressing diverse clinical applications such as interpreting electrocardiograms, detecting dementia, cardiovascular diseases, or predicting the prognosis and survival rates for breast cancer or melanomas. By adopting Machine Learning Techniques (MLT) into medical analysis, diagnostic accuracy is increased, costs are reduced, and human resources are saved. To date, the effectiveness of MLTs for enhancing joint implant design has not been examined. Our goal of this paper is to check the role nanomaterials play during the design of a machine learning based prosthesis.
Keywords
Prosthesis, Machine Learning, Reinforcement Learning, Joint Implant, Hip Surgery, Amputee
Published online 2/1/2023, 19 pages
Citation: Deepali Salwan and Shri Kant, Nanomaterials in Machine Learning Based Prosthesis, Materials Research Foundations, Vol. 141, pp 353-371, 2023
DOI: https://doi.org/10.21741/9781644902295-14
Part of the book on Emerging Applications of Nanomaterials
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