AIMC Topic: Unnecessary Procedures

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Artificial neural network modeling enhances risk stratification and can reduce downstream testing for patients with suspected acute coronary syndromes, negative cardiac biomarkers, and normal ECGs.

The international journal of cardiovascular imaging Dec 1, 2015
Despite uncertain yield, guidelines endorse routine stress myocardial perfusion imaging (MPI) for patients with suspected acute coronary syndromes, unremarkable serial electrocardiograms, and negative troponin measurements. In these patients, outcome...
Aged Male Female Risk Factors Severity of Illness Index Electrocardiography Predictive Value of Tests Middle Aged Risk Assessment Decision Support Techniques Biomarkers Prognosis Retrospective Studies Humans Neural Networks, Computer Tomography, Emission-Computed, Single-Photon Unnecessary Procedures Coronary Stenosis Myocardial Perfusion Imaging Coronary Artery Disease Acute Coronary Syndrome Coronary Angiography Troponin
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Predicting High Imaging Utilization Based on Initial Radiology Reports: A Feasibility Study of Machine Learning.

Academic radiology Oct 27, 2015
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...
Unnecessary Procedures Radiography, Abdominal Sensitivity and Specificity Tomography, X-Ray Computed Humans Adult Male Machine Learning Support Vector Machine Feasibility Studies Research Report
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The use of hemostatic agents does not prevent hemorrhagic complications of robotic partial nephrectomy.

World journal of urology Mar 29, 2015
PURPOSE: To assess the impact of HA on robotic PN (RPN) outcomes.
Prognosis Retrospective Studies Humans Middle Aged Kidney Neoplasms Follow-Up Studies Postoperative Hemorrhage Nephrectomy France Robotics Unnecessary Procedures Blood Loss, Surgical Female Laparoscopy Hemostatics Male
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Machine Learning in Health Care.

National Bureau of Economic Research bulletin on aging and health Jan 1, 2018
Decision Support Techniques Delivery of Health Care Machine Learning Algorithms Cost-Benefit Analysis Unnecessary Procedures Decision Making, Computer-Assisted Risk Factors Myocardial Infarction Humans
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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 Aug 1, 2016
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...
Unnecessary Procedures Sensitivity and Specificity Canada Brain Injuries, Traumatic Humans Algorithms Machine Learning Brain Injuries Tomography, X-Ray Computed
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