AIMC Topic: Patient Safety

Clear Filters Showing 41 to 50 of 178 articles

Detection of Pacemaker and Identification of MRI-conditional Pacemaker Based on Deep-learning Convolutional Neural Networks to Improve Patient Safety.

Journal of medical systems Jul 31, 2023
With the increased availability of magnetic resonance imaging (MRI) and a progressive rise in the frequency of cardiac device implantation, there is an increased chance that patients with implanted cardiac devices require MRI examination during their...
Neural Networks, Computer Patient Safety Deep Learning Humans Magnetic Resonance Imaging Pacemaker, Artificial
View on PubMed DOI

Use of real-time immersive digital training and educational technologies to improve patient safety during the processing of reusable medical devices: Quo Vadis?

The Science of the total environment Jul 20, 2023
Hospital acquired infections stemming from contaminated reusable medical devices are of increasing concern. This issue is exaggerated with the introduction of complex medical devices like endoscopes and robotic instrumentation. Although medical devic...
Patient Safety Humans Learning Artificial Intelligence Educational Technology
View on PubMed DOI

Large language models encode clinical knowledge.

Nature Jul 12, 2023
Large language models (LLMs) have demonstrated impressive capabilities, but the bar for clinical applications is high. Attempts to assess the clinical knowledge of models typically rely on automated evaluations based on limited benchmarks. Here, to a...
Clinical Competence Natural Language Processing Bias Physicians Computer Simulation Comprehension Medicine Knowledge Patient Safety Licensure Benchmarking Datasets as Topic
View on PubMed DOI

Potentiality of algorithms and artificial intelligence adoption to improve medication management in primary care: a systematic review.

BMJ open Mar 23, 2023
OBJECTIVES: The aim of this study is to investigate the effect of artificial intelligence (AI) and/or algorithms on drug management in primary care settings comparing AI and/or algorithms with standard clinical practice. Second, we evaluated what is ...
Primary Health Care Medication Errors Patient Safety Child Medication Therapy Management Humans Artificial Intelligence
View on PubMed DOI

Patient safety classifications, taxonomies and ontologies: A systematic review on development and evaluation methodologies.

Journal of biomedical informatics Jul 22, 2022
INTRODUCTION: Patient safety classifications/ontologies enable patient safety information systems to receive and analyze patient safety data to improve patient safety. Patient safety classifications/ontologies have been developed and evaluated using ...
Natural Language Processing Biological Ontologies Logic Patient Safety Reproducibility of Results Humans
View on PubMed DOI

Machine learning approach to identify adverse events in scientific biomedical literature.

Clinical and translational science Apr 3, 2022
Monitoring the occurrence of adverse events in the scientific literature is a mandatory process in drug marketing surveillance. This is a very time-consuming and complex task to fulfill the compliance and, most importantly, to ensure patient safety. ...
Drug-Related Side Effects and Adverse Reactions Humans Patient Safety Publications Machine Learning
View on PubMed DOI

A Deep Learning-Based Text Classification of Adverse Nursing Events.

Journal of healthcare engineering Nov 18, 2021
Adverse nursing events occur suddenly, unpredictably, or unexpectedly during course of clinical diagnosis and treatment processes in the hospitals. These events adversely affect the patient's diagnosis and treatment results and even increase the pati...
Patient Safety Humans Deep Learning Hospitals Drug-Related Side Effects and Adverse Reactions Delivery of Health Care
View on PubMed DOI

Developing an Analytical Pipeline to Classify Patient Safety Event Reports Using Optimized Predictive Algorithms.

Methods of information in medicine Oct 31, 2021
BACKGROUND: Patient safety event reports provide valuable insight into systemic safety issues but deriving insights from these reports requires computational tools to efficiently parse through large volumes of qualitative data. Natural language proce...
Bayes Theorem Patient Safety Humans Natural Language Processing Machine Learning Algorithms
View on PubMed DOI

Neglected physical human-robot interaction may explain variable outcomes in gait neurorehabilitation research.

Science robotics Sep 22, 2021
During gait neurorehabilitation, many factors influence the quality of gait patterns, particularly the chosen body-weight support (BWS) device. Consequently, robotic BWS devices play a key role in gait rehabilitation of people with neurological disor...
Humans Calibration Patient Safety Orthotic Devices Male Gait Neurological Rehabilitation Man-Machine Systems Female User-Computer Interface Body Weight Equipment Design Biomechanical Phenomena Robotics Walking
View on PubMed DOI

Bayesian Modeling for the Detection of Adverse Events Underreporting in Clinical Trials.

Drug safety Jul 14, 2021
INTRODUCTION: Safety underreporting is a recurrent issue in clinical trials that can impact patient safety and data integrity. Clinical quality assurance (QA) practices used to detect underreporting rely on on-site audits; however, adverse events (AE...
Bayes Theorem Clinical Trials as Topic Machine Learning Patient Safety Humans
View on PubMed DOI
Popular Topics
Recent Journals