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A machine learning approach for predictive models of adverse events following spine surgery.

The spine journal : official journal of the North American Spine Society
BACKGROUND: Rates of adverse events following spine surgery vary widely by patient-, diagnosis-, and procedure-related factors. It is critical to understand the expected rates of complications and to be able to implement targeted efforts at limiting ...

Deep Learning Preoperatively Predicts Value Metrics for Primary Total Knee Arthroplasty: Development and Validation of an Artificial Neural Network Model.

The Journal of arthroplasty
BACKGROUND: The objective is to develop and validate an artificial neural network (ANN) that learns and predicts length of stay (LOS), inpatient charges, and discharge disposition before primary total knee arthroplasty (TKA). The secondary objective ...

Predictive Analysis of First Abbreviated New Drug Application Submission for New Chemical Entities Based on Machine Learning Methodology.

Clinical pharmacology and therapeutics
Generic drug products are approved by the US Food and Drug Administration (FDA) through Abbreviated New Drug Applications (ANDAs). The ANDA review and approval involves multiple offices across the FDA. Forecasting ANDA submissions can critically info...

Concepts in U.S. Food and Drug Administration Regulation of Artificial Intelligence for Medical Imaging.

AJR. American journal of roentgenology
Although extensive attention has been focused on the enormous potential of artificial intelligence (AI) technology, a major question remains: how should this fundamentally new technology be regulated? The purpose of this article is to provide an ove...

A Road Map for Translational Research on Artificial Intelligence in Medical Imaging: From the 2018 National Institutes of Health/RSNA/ACR/The Academy Workshop.

Journal of the American College of Radiology : JACR
Advances in machine learning in medical imaging are occurring at a rapid pace in research laboratories both at academic institutions and in industry. Important artificial intelligence (AI) tools for diagnostic imaging include algorithms for disease d...

Natural Language Processing for Identification of Incidental Pulmonary Nodules in Radiology Reports.

Journal of the American College of Radiology : JACR
PURPOSE: To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations.

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

Nature medicine
With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in the United States. Lung cancer screening using low-dose computed tomography has been shown to reduce mortality by 20-43% and is now included in US scree...

Robotics in Dental Implantology.

Oral and maxillofacial surgery clinics of North America
Robotic surgery is no longer a fiction and its clinical applications are rapidly developing. Robotic surgery is increasingly used because of its minimal invasiveness. This article provides an overview of robotic surgery and its current applications i...