Real-World Implementation of Artificial Intelligence/Machine Learning for Managing Surgical Spine Patients at 2 Academic Health Care Systems

被引：1

作者：

Habboub, Ghaith ^{[1
]}

Berven, Sigurd ^{[2
]}

Ames, Christopher ^{[3
]}

Peterson, Thomas ^{[2
]}

Mroz, Thomas ^{[1
]}

机构：

[1] Cleveland Clin, Ctr Spine Hlth, Cleveland, OH USA

[2] UCSF, Dept Orthoped Surg, Med Ctr, San Francisco, CA USA

[3] Univ Calif San Francisco, Dept Neurol Surg, San Francisco, CA USA

来源：

INTERNATIONAL JOURNAL OF SPINE SURGERY | 2023年 / 17卷

关键词：

artificial intelligence; predictive modeling; spine surgery; PREOPERATIVE PREDICTIVE MODEL; DEFORMITY; COMPLICATIONS; SURGEONS;

D O I：

10.14444/8506

中图分类号：

R61 [外科手术学];

学科分类号：

摘要：

Decision-making in spine surgery is complex due to patients' heterogeneity and complexity of spinal pathologies and the various surgical options applied to a given pathology. Artificial intelligence/machine learning algorithms provide an opportunity to improve patient selection, surgical planning, and outcomes. The purpose of this article is to present the experience and applications of in spine surgery at 2 large academic health care systems.

引用

页码：S11 / S17

页数：7

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