Clinical and Research Medical Applications of Artificial Intelligence

被引:65
作者
Ramkumar, Prem N. [1 ,2 ]
Kunze, Kyle N. [3 ]
Haeberle, Heather S. [1 ,3 ]
Karnuta, Jaret M. [1 ]
Luu, Bryan C. [1 ,4 ]
Nwachukwu, Benedict U. [3 ]
Williams, Riley J. [3 ]
机构
[1] Cleveland Clin, Orthopaed Machine Learning Lab, Cleveland, OH 44118 USA
[2] Brigham & Womens Hosp, Dept Orthopaed Surg, 75 Francis St, Boston, MA 02115 USA
[3] Hosp Special Surg, Dept Orthopaed Surg, 535 E 70th St, New York, NY 10021 USA
[4] Baylor Coll Med, Dept Orthopaed Surg, Houston, TX 77030 USA
关键词
CLASSIFICATION;
D O I
10.1016/j.arthro.2020.08.009
中图分类号
R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学(修复外科学)];
学科分类号
摘要
Artificial intelligence (AI), including machine learning (ML), has transformed numerous industries through newfound efficiencies and supportive decision-making. With the exponential growth of computing power and large datasets, AI has transitioned from theory to reality in teaching machines to automate tasks without human supervision. AI-based computational algorithms analyze ?training sets? using pattern recognition and learning from inputted data to classify and predict outputs that otherwise could not be effectively analyzed with human processing or standard statistical methods. Though widespread understanding of the fundamental principles and adoption of applications have yet to be achieved, recent applications and research efforts implementing AI have demonstrated great promise in predicting future injury risk, interpreting advanced imaging, evaluating patient-reported outcomes, reporting value-based metrics, and augmenting telehealth. With appreciation, caution, and experience applying AI, the potential to automate tasks and improve data-driven insights may be realized to fundamentally improve patient care. The purpose of this review is to discuss the pearls, pitfalls, and applications associated with AI.
引用
收藏
页码:1694 / 1697
页数:4
相关论文
共 19 条
[1]   Deep Learning for Detection of Complete Anterior Cruciate Ligament Tear [J].
Chang, Peter D. ;
Wong, Tony T. ;
Rasiej, Michael J. .
JOURNAL OF DIGITAL IMAGING, 2019, 32 (06) :980-986
[2]   Dermatologist-level classification of skin cancer with deep neural networks [J].
Esteva, Andre ;
Kuprel, Brett ;
Novoa, Roberto A. ;
Ko, Justin ;
Swetter, Susan M. ;
Blau, Helen M. ;
Thrun, Sebastian .
NATURE, 2017, 542 (7639) :115-+
[3]   Deep convolutional neural network-based detection of meniscus tears: comparison with radiologists and surgery as standard of reference [J].
Fritz, Benjamin ;
Marbach, Giuseppe ;
Civardi, Francesco ;
Fucentese, Sandro F. ;
Pfirrmann, Christian W. A. .
SKELETAL RADIOLOGY, 2020, 49 (08) :1207-1217
[4]   Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs [J].
Gulshan, Varun ;
Peng, Lily ;
Coram, Marc ;
Stumpe, Martin C. ;
Wu, Derek ;
Narayanaswamy, Arunachalam ;
Venugopalan, Subhashini ;
Widner, Kasumi ;
Madams, Tom ;
Cuadros, Jorge ;
Kim, Ramasamy ;
Raman, Rajiv ;
Nelson, Philip C. ;
Mega, Jessica L. ;
Webster, R. .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2016, 316 (22) :2402-2410
[5]   Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Review [J].
Haeberle, Heather S. ;
Helm, James M. ;
Navarro, Sergio M. ;
Karnuta, Jaret M. ;
Schaffer, Jonathan L. ;
Callaghan, John J. ;
Mont, Michael A. ;
Kamath, Atul F. ;
Krebs, Viktor E. ;
Ramkumar, Prem N. .
JOURNAL OF ARTHROPLASTY, 2019, 34 (10) :2201-2203
[6]   Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network [J].
Hannun, Awni Y. ;
Rajpurkar, Pranav ;
Haghpanahi, Masoumeh ;
Tison, Geoffrey H. ;
Bourn, Codie ;
Turakhia, Mintu P. ;
Ng, Andrew Y. .
NATURE MEDICINE, 2019, 25 (01) :65-+
[7]   Machine Learning and Artificial Intelligence: Definitions, Applications, and Future Directions [J].
Helm, J. Matthew ;
Swiergosz, Andrew M. ;
Haeberle, Heather S. ;
Karnuta, Jaret M. ;
Schaffer, Jonathan L. ;
Krebs, Viktor E. ;
Spitzer, Andrew, I ;
Ramkumar, Prem N. .
CURRENT REVIEWS IN MUSCULOSKELETAL MEDICINE, 2020, 13 (01) :69-76
[8]  
Karnuta J, ORTHOP J SPORT MED
[9]   Machine Learning Outperforms Regression Analysis to Predict Next-Season Major League Baseball Player Injuries: Epidemiology and Validation of 13,982 Player-Years From Performance and Injury Profile Trends, 2000-2017 [J].
Karnuta, Jaret M. ;
Luu, Bryan C. ;
Haeberle, Heather S. ;
Saluan, Paul M. ;
Frangiamore, Salvatore J. ;
Stearns, Kim L. ;
Farrow, Lutul D. ;
Nwachukwu, Benedict U. ;
Verma, Nikhil N. ;
Makhni, Eric C. ;
Schickendantz, Mark S. ;
Ramkumar, Prem N. .
ORTHOPAEDIC JOURNAL OF SPORTS MEDICINE, 2020, 8 (11)
[10]  
Luu B, ORTHOP J SPORT MED