AIMC Topic: Patient Safety

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

Journal of biomedical informatics
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 ...

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

Clinical and translational science
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. ...

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

Journal of healthcare engineering
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...

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

Methods of information in medicine
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...

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

Science robotics
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...

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

Drug safety
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...

Evaluating eligibility criteria of oncology trials using real-world data and AI.

Nature
There is a growing focus on making clinical trials more inclusive but the design of trial eligibility criteria remains challenging. Here we systematically evaluate the effect of different eligibility criteria on cancer trial populations and outcomes ...

Assessing Drug Development Risk Using Big Data and Machine Learning.

Cancer research
Identifying new drug targets and developing safe and effective drugs is both challenging and risky. Furthermore, characterizing drug development risk, the probability that a drug will eventually receive regulatory approval, has been notoriously hard ...