Künstliche Intelligenz und Ausblick auf Anwendungsfelder in der Pseudarthrosentherapie

人工智能 计算机科学 人工神经网络 深度学习 机器学习 领域(数学) 鉴定(生物学) 学习迁移 数据科学 数学 植物 纯数学 生物
作者
Marie K. Reumann,Benedikt J. Braun,Maximilian F. S. J. Menger,Fabian Springer,Johann Jazewitsch,Tobias Schwarz,Andreas K. Nussler,Tina Histing,Mika F. Rollmann
标识
DOI:10.1007/s00113-022-01202-y
摘要

Methods of artificial intelligence (AI) have found applications in many fields of medicine within the last few years. Some disciplines already use these methods regularly within their clinical routine. However, the fields of application are wide and there are still many opportunities to apply these new AI concepts. This review article gives an insight into the history of AI and defines the special terms and fields, such as machine learning (ML), neural networks and deep learning. The classical steps in developing AI models are demonstrated here, as well as the iteration of data rectification and preparation, the training of a model and subsequent validation before transfer into a clinical setting are explained. Currently, musculoskeletal disciplines implement methods of ML and also neural networks, e.g. for identification of fractures or for classifications. Also, predictive models based on risk factor analysis for prevention of complications are being initiated. As non-union in bone is a rare but very complex disease with dramatic socioeconomic impact for the healthcare system, many open questions arise which could be better understood by using methods of AI in the future. New fields of research applying AI models range from predictive models and cost analysis to personalized treatment strategies.
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