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A machine learning based approach for identifying traumatic brain injury patients for whom a head CT scan can be avoided.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Head CT scan is more often used to evaluate patients with suspected traumatic brain injury (TBI). However, the use of head CT scans in evaluating TBI is costly with low value endeavor. In this paper, we propose a new algorithm and a set of features t...

Predicting High Imaging Utilization Based on Initial Radiology Reports: A Feasibility Study of Machine Learning.

Academic radiology
RATIONALE AND OBJECTIVES: Imaging utilization has significantly increased over the last two decades, and is only recently showing signs of moderating. To help healthcare providers identify patients at risk for high imaging utilization, we developed a...

High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision.

Radiology
Purpose To develop a machine learning model that allows high-risk breast lesions (HRLs) diagnosed with image-guided needle biopsy that require surgical excision to be distinguished from HRLs that are at low risk for upgrade to cancer at surgery and t...