Zeitschrift fur Gerontologie und Geriatrie
May 25, 2016
BACKGROUND: The development of social assistive robots is an approach with the intention of preventing and detecting falls among seniors. There is a need for a relatively low-cost mobile robot with an arm and a gripper which is small enough to naviga...
Advancements in information, communication, and sensor technologies have led to new opportunities in medical care and education. Patients in general prefer visiting the nearest clinic, attempt to avoid waiting for treatment, and have unequal preferen...
OBJECTIVE: One of the main goals of brain-machine interface (BMI) research is to restore function to people with paralysis. Currently, multiple BMI design features are being investigated, based on various input modalities (externally applied and surg...
International journal of obstetric anesthesia
Aug 1, 2025
BACKGROUND: Recent studies evaluating frequently asked questions (FAQs) on labor epidural analgesia (LEA) only used generic questions without incorporating detailed clinical information that reflects patient-specific inputs. We investigated the perfo...
International journal of medical informatics
Jul 1, 2025
BACKGROUND: Digital health interventions targeting substance use disorders are being increasingly implemented. Data science methodology has the potential to enhance involvement and efficacy of these interventions, though application may raise ethical...
BACKGROUND: Over 96% of adult women face health issues, with 70% experiencing conditions like infections. Mobile health education is increasingly popular but faces challenges in personalization and readability. Artificial intelligence (AI) chatbots p...
BackgroundLet's Talk Tech (LTT) is a self-administered web intervention for people with memory loss and their care partners that supports decision-making about digital health technologies. In past work, dyads wanted to share LTT preference reports wi...
BACKGROUND: Artificial intelligence (AI) could improve accuracy and efficiency of breast cancer screening. However, many women distrust AI in health care, potentially jeopardizing breast cancer screening participation rates. The aim was to quantify c...
Machine learning (ML)-based risk prediction models hold the potential to support the health-care setting in several ways; however, use of such models is scarce. We aimed to review health-care professional (HCP) and patient perceptions of ML risk pred...
In an analysis of artificially intelligent systems for medical diagnostics and treatment planning we argue that patients should be able to exercise a right to withdraw from AI diagnostics and treatment planning for reasons related to (1) the physicia...
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