Artificial Intelligence and Machine Learning in Orthopedic Surgery: Applications, Current State, and Future Prospective

Background and aims: Artificial intelligence (AI) and machine learning (ML) have grown considerablyin several major fields of medicine. Furthermore, with the unprecedented advancementof data aggregation and deep learning algorithms, AI and ML are reforming the practice of medicine.In particular, the field of orthopedics is uniquely suited to harness the power of big dataand provide critical insights into elevating many facets of orthopedic surgery. The purpose of thisreview is to provide an update on the developments of AI and ML and evaluate the applicationsof AI and ML in the field of orthopedic surgery.Method: This study is a narrative review of published articles in the field of AI and ML applicationsin orthopedic surgery. To obtain the resources, the keywords of “orthopedic surgery”,“artificial intelligence” and “machine learning” were used in databases such as Google Scholar,Science Direct, PubMed, Wiley, and so forth.Results: AI and ML applications in the field of orthopedic surgery could be deployed in threecategories; clinical diagnosis, predicting postoperative outcomes, and complications. Clinical diagnosisthrough image interpretation is the most popular area of AI. For instance, AI algorithmshave been applied to various medical conditions such as bone fractures which AI performed aswell as or better than orthopedic surgeons in detecting the fractures. This can also be done byintegrating the use of information from a patient’s medical records, allowing the program to determinethe most appropriate patient-specific imaging examination and surgical protocol. AI alsoimproves quantitative image analysis by allowing automatic segmentation of the area of interest.Another major use of AI in healthcare is predicting the postoperative outcomes of patients basedon a clinical dataset, genomic information, medical images, and surgical approach. Also, Riskassessment and outcome prediction have always been challenging in clinical medicine. AI offersa new direction that could potentially overcome these challenges. Moreover, in orthopedics, MLcan be used to guide the management of patients by providing a patient-specific predicted rate ofpostoperative complications.Conclusion: Orthopedic surgery is one of the most technologically innovative fields in medicine.Nevertheless, AI and ML adoption is still in the preliminary phase in orthopedics. Although theuse of AI has developed in the vast majority of medical aspects rapidly, orthopedic surgery hasbeen slower to do so. The AI technique can help making a diagnosis or decision in orthopedicsurgery, for example ML approaches could be used to create a treatment decision support systemwith the intention of improving diagnostic accuracy and reducing costs. Further advances couldenable the combination of AI and clinicians to make more rigorous classifications than humandecision-making alone. Ultimately, there has been a recent surge in new research, emphasizingthe need for further study in the field of orthopedic surgery.

کلیدواژه ها:

Orthopedic Surgery ، Artificial Intelligence ، Machine Learning