AIMC Topic: Nurses
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The views of physicians and nurses on the potentials of an electronic assessment system for recognizing the needs of patients in palliative care.
BMC palliative care
Apr 4, 2020
OBJECTIVES: Patients in oncological and palliative care (PC) often have complex needs, which require a comprehensive treatment approach. The assessment of patient-reported outcomes (PROs) has been shown to improve identification of patient needs and ...
Unsupervised Machine Learning of Topics Documented by Nurses about Hospitalized Patients Prior to a Rapid-Response Event.
Applied clinical informatics
Dec 18, 2019
BACKGROUND: In the hospital setting, it is crucial to identify patients at risk for deterioration before it fully develops, so providers can respond rapidly to reverse the deterioration. Rapid response (RR) activation criteria include a subjective co...
ICU staffing feature phenotypes and their relationship with patients' outcomes: an unsupervised machine learning analysis.
Intensive care medicine
Oct 8, 2019
PURPOSE: To study whether ICU staffing features are associated with improved hospital mortality, ICU length of stay (LOS) and duration of mechanical ventilation (MV) using cluster analysis directed by machine learning.
Using the MEDiPORT humanoid robot to reduce procedural pain and distress in children with cancer: A pilot randomized controlled trial.
Pediatric blood & cancer
Jun 12, 2018
BACKGROUND: Subcutaneous port needle insertions are painful and distressing for children with cancer. The interactive MEDiPORT robot has been programmed to implement psychological strategies to decrease pain and distress during this procedure. This s...
The digital generation and nursing robotics: A netnographic study about nursing care robots posted on social media.
Nursing inquiry
Oct 11, 2016
The aim of this study was to present the functionality and design of nursing care robots as depicted in pictures posted on social media. A netnographic study was conducted using social media postings over a period of 3 years. One hundred and Seventy-...
Expanding the occupational health methodology: A concatenated artificial neural network approach to model the burnout process in Chinese nurses.
Ergonomics
Jul 31, 2015
UNLABELLED: Artificial neural networks are sophisticated modelling and prediction tools capable of extracting complex, non-linear relationships between predictor (input) and predicted (output) variables. This study explores this capacity by modelling...
The first step in using a robot in brain injury rehabilitation: patients' and health-care professionals' perspective.
Disability and rehabilitation. Assistive technology
Apr 28, 2014
PURPOSE: To evaluate the usability of a mobile telepresence robot (MTR) in a hospital training apartment (HTA). The MTR was manoeuvred remotely and was used for communication when assessing independent living skills, and for security monitoring of co...
Development and Validation of a Scale for Nurses' Ethical Awareness in The Use of Artificial Intelligence: A Methodological Study.
Nursing & health sciences
Jun 1, 2025
The integration of artificial intelligence in nursing practice presents significant ethical challenges that require a comprehensive assessment framework. This study aimed to develop and validate a scale to measure nurses' ethical awareness regarding ...
Using machine learning models to identify severe subjective cognitive decline and related factors in nurses during the menopause transition: a pilot study.
Menopause (New York, N.Y.)
Apr 1, 2025
OBJECTIVE: This study aims to develop and validate a machine learning model for identifying individuals within the nursing population experiencing severe subjective cognitive decline (SCD) during the menopause transition, along with their associated ...
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