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Patient Safety

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Can Unified Medical Language System-based semantic representation improve automated identification of patient safety incident reports by type and severity?

Journal of the American Medical Informatics Association : JAMIA Oct 1, 2020
OBJECTIVE: The study sought to evaluate the feasibility of using Unified Medical Language System (UMLS) semantic features for automated identification of reports about patient safety incidents by type and severity.
Humans Patient Safety Support Vector Machine Semantics Unified Medical Language System Medical Errors Natural Language Processing Risk Management Datasets as Topic
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Comparison of Machine Learning Algorithms for Classifying Adverse-Event Related 30-Day Hospital Readmissions: Potential Implications for Patient Safety.

Studies in health technology and informatics Jun 26, 2020
Studies in the last decade have focused on identifying patients at risk of readmission using predictive models, in an objective to decrease costs to the healthcare system. However, real-time models specifically identifying readmissions related to hos...
Humans Patient Readmission Machine Learning Patient Safety Hospitals
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Development of an Alarm Algorithm, With Nanotechnology Multimodal Sensor, to Predict Impending Infusion Failure and Improve Safety of Peripheral Intravenous Catheters in Neonates.

Advances in neonatal care : official journal of the National Association of Neonatal Nurses Jun 1, 2020
BACKGROUND: Peripheral intravenous catheters connected to an infusion pump are necessary for the delivery of fluids, nutrition, and medications to hospitalized neonates but are not without complications. These adverse events contribute to hospital-ac...
Nanotechnology Patient Safety Infusion Pumps Clinical Alarms Infant, Newborn Humans Catheterization, Peripheral Artificial Intelligence Equipment Failure Monitoring, Physiologic Infusions, Intravenous
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On Patient Safety: The Lure of Artificial Intelligence-Are We Jeopardizing Our Patients' Privacy?

Clinical orthopaedics and related research Apr 1, 2020
Humans Artificial Intelligence Patient Safety Privacy Forms and Records Control United States Health Insurance Portability and Accountability Act Health Records, Personal
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Follow-Up on the Use of Machine Learning in Clinical Quality Assurance: Can We Detect Adverse Event Under-Reporting in Oncology Trials?

Drug safety Mar 1, 2020
Clinical Trials as Topic Machine Learning Adverse Drug Reaction Reporting Systems Quality Assurance, Health Care Humans Antineoplastic Agents Patient Safety Quality Indicators, Health Care Neoplasms Drug-Related Side Effects and Adverse Reactions Research Report
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Introducing artificial intelligence in acute psychiatric inpatient care: qualitative study of its use to conduct nursing observations.

Evidence-based mental health Feb 1, 2020
BACKGROUND: All patients admitted to an acute inpatient mental health unit must have nursing observations carried out at night either hourly or every 15 minutes, to ascertain that they are safe and breathing. However, while this practice ensures pati...
Psychiatric Department, Hospital Observation Psychiatric Nursing Artificial Intelligence Patient Safety Adult Qualitative Research Monitoring, Physiologic Acute Disease Humans
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How the FDA Regulates AI.

Academic radiology Jan 1, 2020
Recent years have seen digital technologies increasingly leveraged to multiply conventional imaging modalities' diagnostic power. Artificial intelligence (AI) is most prominent among these in the radiology space, touted as the "stethoscope of the 21s...
Humans Artificial Intelligence Workflow Patient Safety United States United States Food and Drug Administration Radiology
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Using convolutional neural networks to identify patient safety incident reports by type and severity.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
OBJECTIVE: To evaluate the feasibility of a convolutional neural network (CNN) with word embedding to identify the type and severity of patient safety incident reports.
Support Vector Machine Risk Management Feasibility Studies Humans Neural Networks, Computer Classification Patient Safety Medical Errors
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Reducing drug prescription errors and adverse drug events by application of a probabilistic, machine-learning based clinical decision support system in an inpatient setting.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2019
BACKGROUND: Drug prescription errors are made, worldwide, on a daily basis, resulting in a high burden of morbidity and mortality. Existing rule-based systems for prevention of such errors are unsuccessful and associated with substantial burden of fa...
Medication Errors Drug Therapy, Computer-Assisted Medication Systems, Hospital Medical Order Entry Systems Drug-Related Side Effects and Adverse Reactions Machine Learning Israel Algorithms Academic Medical Centers Patient Safety Prospective Studies Decision Support Systems, Clinical Humans
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The Role of Generative Adversarial Networks in Radiation Reduction and Artifact Correction in Medical Imaging.

Journal of the American College of Radiology : JACR Sep 1, 2019
Adversarial networks were developed to complete powerful image-processing tasks on the basis of example images provided to train the networks. These networks are relatively new in the field of deep learning and have proved to have unique strengths th...
Deep Learning Humans Positron-Emission Tomography Forecasting Magnetic Resonance Imaging Artifacts Artificial Intelligence Diagnostic Imaging Patient Safety Radiation Exposure Tomography, X-Ray Computed
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