Aiming to eliminate a labor shortage caused by the aging of society, many kinds of service robots are under development. Nursing care for the elderly is considered as a typical application of service robots, especially in Japan. Elderly care robots or robotic care device must be designed with safety, but not a few manufacturers are inexperienced in designing and manufacturing them on the basis of safety. In this paper, we introduce a risk assessment assistance tool for robotic care device targeted for inexperienced manufacturers of risk assessment.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Risk factors of short-term poor functional outcomes and long-term durability of ruptured large or giant intracranial aneurysms.
J Neurosurg
January 2025
13Department of Neurosurgery, Shimane Prefectural Central Hospital, Shimane, Japan.
Objective: Aneurysmal subarachnoid hemorrhage (SAH) is associated with high morbidity and mortality rates. In particular, functional outcomes of SAH caused by large or giant (≥ 10 mm) ruptured intracranial aneurysms are worsened by high procedure-related complication rates. However, studies describing the risk factors for poor functional outcomes specific to ruptured large/giant aneurysms are sparse.
View Article and Find Full Text PDFPM2.5 Speciation chemicals and Neonatal Respiratory Distress Syndrome (RDS): Uncovering the Interactions of Maternal Health, Environmental metal pollutants, and Sociodemographic Factors.
J Occup Environ Med
January 2025
Department of Biostatistics, Florida International University, Miami, FL, United States.
Objective: To assess factors influencing Neonatal Respiratory Distress Syndrome (RDS) risk, incorporating maternal demographics, behaviors, medical conditions, pregnancy-related factors, and PM2.5 speciation pollutants exposures.
Methods: Using Florida de-identified birth records, logistic regression analyses were conducted to assess associations between maternal exposure to PM2.
Use of Hearing Aids Embedded with Inertial Sensors and Artificial Intelligence to Identify Patients at Risk for Falling.
Otol Neurotol
February 2025
Department of Otolaryngology-Head and Neck Surgery.
Objective: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.
Study Design: Prospective, double-blinded, observational study of fall risk scores between trained observers and those of IMU-HAs.
Setting: Tertiary referral center.
A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment.
PLoS One
January 2025
College of Business, Southern University of Science and Technology, Shenzhen, China.
In credit risk assessment, unsupervised classification techniques can be introduced to reduce human resource expenses and expedite decision-making. Despite the efficacy of unsupervised learning methods in handling unlabeled datasets, their performance remains limited owing to challenges such as imbalanced data, local optima, and parameter adjustment complexities. Thus, this paper introduces a novel hybrid unsupervised classification method, named the two-stage hybrid system with spectral clustering and semi-supervised support vector machine (TSC-SVM), which effectively addresses the unsupervised imbalance problem in credit risk assessment by targeting global optimal solutions.
View Article and Find Full Text PDFDevelopment of endosome-related gene signature for the prediction of prognosis and therapeutic response in breast cancer.
Medicine (Baltimore)
January 2025
Department of Breast, Haining Maternity and Child Health Care Hospital, Haining, Zhejieng, China.
Endosomes play a pivotal role in cellular biology, orchestrating processes such as endocytosis, molecular trafficking, signal transduction, and recycling of cellular materials. This study aims to construct an endosome-related gene (ERG)-derived risk signature for breast cancer prognosis. Transcriptomic and clinical data were retrieved from The Cancer Genome Atlas and the University of California Santa Cruz databases to build and validate the model.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!