AIMC Topic: Family
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Study protocol for the Rainbow Austrian Longitudinal Family (RALF) study: a longitudinal, multi-method, multi-rater investigation of risk and resilience factors in Austrian LGBTQ+ parent families.
BMC psychology
May 26, 2025
BACKGROUND: Research on LGBTQ+ parent families is evolving to include a growing range of family systems, identities, methodologies, and topics. However, studies that examine minority-specific risk and resilience factors and their associations with wi...
The Impact of Telepresence Robots on Family Caregivers and Residents in Long-Term Care.
International journal of environmental research and public health
May 1, 2025
Telepresence robots can enhance social connection and support person-centered care in long-term care (LTC) homes. This study evaluates their impact in facilitating virtual visits between family caregivers and older residents in Canadian LTC homes. Te...
Revolutionizing Intensive Care Unit Care: A Scoping Review of Multimodal Family Engagement Technologies.
Critical care nursing clinics of North America
Apr 7, 2025
This scoping review systematically examines the emerging field of multimodal family engagement technologies in intensive care units (ICUs). Despite significant advancements in medical technology, family engagement remains an underutilized resource in...
Artificial intelligence chatbots: Are they a reliable source for patients and families in pediatric neuro-oncology?
Pediatric blood & cancer
Jul 5, 2024
Perspective analysis of assistive robots for elderly in India.
Disability and rehabilitation. Assistive technology
Mar 7, 2024
PURPOSE: Assistive technology for elderly are advancing, and this study aimed to analyse the Indian perspective on utilising assistive robot technology for aiding elderly individuals.
Existing Barriers Faced by and Future Design Recommendations for Direct-to-Consumer Health Care Artificial Intelligence Apps: Scoping Review.
Journal of medical Internet research
Dec 18, 2023
BACKGROUND: Direct-to-consumer (DTC) health care artificial intelligence (AI) apps hold the potential to bridge the spatial and temporal disparities in health care resources, but they also come with individual and societal risks due to AI errors. Fur...
Machine learning-based approach for predicting low birth weight.
BMC pregnancy and childbirth
Nov 20, 2023
BACKGROUND: Low birth weight (LBW) has been linked to infant mortality. Predicting LBW is a valuable preventative tool and predictor of newborn health risks. The current study employed a machine learning model to predict LBW.
Examining the Impact of Assistive Technology on Psychological Health, Family Education, and Curriculum Research in Japan: Insights from Artificial Intelligence.
Journal of autism and developmental disorders
Sep 23, 2023
This study aims to analyze the effect of psychological health based on artificial intelligence agent technology on the implementation effect of Japanese family education. By combining mobile agent technology and education thought, the system structur...
PhenoBERT: A Combined Deep Learning Method for Automated Recognition of Human Phenotype Ontology.
IEEE/ACM transactions on computational biology and bioinformatics
Apr 3, 2023
Automated recognition of Human Phenotype Ontology (HPO) terms from clinical texts is of significant interest to the field of clinical data mining. In this study, we develop a combined deep learning method named PhenoBERT for this purpose. PhenoBERT u...
What do individuals with visual impairment need and want from a dialogue-based digital assistant?
Clinical & experimental optometry
Jan 29, 2023
CLINICAL SIGNIFICANCE: Optometrists are well-placed to provide helpful advice and guidance to patients with visual impairment but may not know how best to do this. The availability of a reliable and comprehensive conversational agent to which patient...
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