This study aimed to identify barriers and facilitators to older adults' acceptance of socially assistive robots from a stakeholder perspective. We enlisted 36 distinct stakeholders, including older adult, nurses, retirement home managers, and employe...
Several studies reported that20% of patients were unhappy with the outcome of their total knee arthroplasty (TKA). Having commenced robot assist TKA whilst maintaining the goal of implanting the prosthesis to a neutral mechanical axis, we reviewed ou...
BACKGROUND: Physicians are currently overwhelmed by administrative tasks and spend very little time in consultations with patients, which hampers health literacy, shared decision-making, and treatment adherence.
Fundamental principles underlying computation in multi-scale brain networks illustrate how multiple brain areas and their coordinated activity give rise to complex cognitive functions. Whereas brain activity has been studied at the micro- to meso-sca...
IMPORTANCE: Limited sharing of data sets that accurately represent disease and patient diversity limits the generalizability of artificial intelligence (AI) algorithms in health care.
IISE transactions on occupational ergonomics and human factors
Nov 11, 2023
OCCUPATIONAL APPLICATIONSOur survey of 100 manufacturing facilities revealed statistically significant differences among company types in their perceptions of cost savings, productivity gains, and safety improvements as benefits of robotic implementa...
Given the increasing concern about the destructive impact of sympathetic activities on the Earth, involving the next generation in environmental conservation is crucial. Therefore, this study aims to explore how artificial intelligence (AI) and virtu...
This study proposes a novel multi-stage multi-attribute group decision making method under a probabilistic linguistic environment considering the development state and trend of alternatives. First, the probabilistic linguistic term set (PLTS) is used...
Neural networks : the official journal of the International Neural Network Society
Oct 9, 2023
The problem of reducing processing time of large deep learning models is a fundamental challenge in many real-world applications. Early exit methods strive towards this goal by attaching additional Internal Classifiers (ICs) to intermediate layers of...
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