AIMC Topic: Austria
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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...
Ambiguous animals, ambivalent carers and arbitrary care collectives: Re-theorizing resistance to social robots in healthcare.
Social science & medicine (1982)
Dec 2, 2024
Many countries are under pressure because of lack of healthcare staff to provide care to an increasingly aged population. Potential solutions are often sought through technological innovation, including social robots to cater to the patients' emotion...
Machine learning prediction of unexpected readmission or death after discharge from intensive care: A retrospective cohort study.
Journal of clinical anesthesia
Oct 14, 2024
BACKGROUND: Intensive care units (ICUs) harbor the sickest patients with the utmost needs of medical care. Discharge from ICU needs to consider the reason for admission and stability after ICU care. Organ dysfunction or instability after ICU discharg...
Attitude of aspiring orthopaedic surgeons towards artificial intelligence: a multinational cross-sectional survey study.
Archives of orthopaedic and trauma surgery
Aug 10, 2024
INTRODUCTION: The purpose of this study was to evaluate the perspectives of aspiring orthopaedic surgeons on artificial intelligence (AI), analysing how gender, AI knowledge, and technical inclination influence views on AI. Additionally, the extent t...
Shaping future practices: German-speaking medical and dental students' perceptions of artificial intelligence in healthcare.
BMC medical education
Aug 6, 2024
BACKGROUND: The growing use of artificial intelligence (AI) in healthcare necessitates understanding the perspectives of future practitioners. This study investigated the perceptions of German-speaking medical and dental students regarding the role o...
Coaching Robots for Older Seniors: Do They Get What They Expect? Insights from an Austrian Study.
International journal of environmental research and public health
Feb 8, 2023
To support the increasing number of older people, new (assistive) technologies are constantly being developed. For these technologies to be used successfully, future users need to be trained. Due to demographic change, this will become difficult in t...
The use of a UV-C disinfection robot in the routine cleaning process: a field study in an Academic hospital.
Antimicrobial resistance and infection control
May 29, 2021
BACKGROUND: Environmental surface decontamination is a crucial tool to prevent the spread of infections in hospitals. However, manual cleaning and disinfection may be insufficient to eliminate pathogens from contaminated surfaces. Ultraviolet-C (UV-C...
Clustering suicides: A data-driven, exploratory machine learning approach.
European psychiatry : the journal of the Association of European Psychiatrists
Sep 7, 2019
Methods of suicide have received considerable attention in suicide research. The common approach to differentiate methods of suicide is the classification into "violent" versus "non-violent" method. Interestingly, since the proposition of this dichot...
Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study.
The Lancet. Digital health
Aug 27, 2019
BACKGROUND: Development of valid, non-invasive biomarkers for parkinsonian syndromes is crucially needed. We aimed to assess whether non-invasive diffusion-weighted MRI can distinguish between parkinsonian syndromes using an automated imaging approac...
Development and Validation of the Automated Imaging Differentiation in Parkinsonism (AID-P): A Multi-Site Machine Learning Study.
The Lancet. Digital health
Aug 27, 2019
BACKGROUND: There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian syndromes. The current 17-site, international study assesses whether non-invasive diffusion MRI (dMRI) can distinguish between Parkinsonian syndromes.
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