Authors : Basavaraj. G; Manoj. M.P; Rachana. H. B; Chetan Kumar G S

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/34m2e3vd

Scribd : https://tinyurl.com/mw9x85yc

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY1495

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Artificial intelligence (AI) is being used more and more in numerous fields, and the medical industry is no exception. AI is demonstrating potential as a helpful tool in all facets of patient care pathways, including research in healthcare. Due to the practically exponential expansion in computer processing power, cloud computing, and the invention and improvement of software algorithms specifically designed for medical tasks, artificial intelligence (AI) systems are becoming more and more significant in the fields of medicine and orthopaedic surgery. Machine-based integration of imaging studies is particularly ripe for the field of orthopaedic disorders because of the extensive role of technologies like medical imaging that bring high sensitivity, specificity, and positive/negative prognostic value to the management of orthopaedic disorders, among other applications. In orthopaedic surgery, practical applications include real-time rehabilitation monitoring and surgical training; predictive models of clinical and patient-reported outcome measures, such as calculating mortality rates and length of hospital stay; and diagnostics, such as fracture recognition and tumor detection. This study aims to outline current clinical uses of AI in orthopaedic surgery and to provide a thorough grasp of AI and its subfields.

Keywords : Artificial Intelligence, Orthopaedics, Orthopaedic Surgery, Machine Learning, Deep Learning.

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