ORCID Profile
0000-0001-8559-5610
Current Organisations
Monash University
,
Monash University - Caulfield Campus
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Publisher: Springer Berlin Heidelberg
Date: 2014
Publisher: ACM
Date: 08-05-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: ACM
Date: 09-10-2023
Publisher: Hindawi Limited
Date: 22-09-2022
DOI: 10.1111/PEDI.13416
Abstract: To examine the prevalence, time trends, and risk factors of diabetic retinopathy (DR) among youth with type 1 diabetes (T1D) from 11 countries (Australia, Austria, Denmark, England, Germany, Italy, Luxemburg, Netherlands, Slovenia, United States, and Wales). Data on in iduals aged 10-21 years with T1D for >1 year during the period 2000-2020 were analyzed. We used a cross-sectional design using the most recent year of visit to investigate the time trend. For datasets with longitudinal data, we aggregated the variables per participant and observational year, using data of the most recent year to take the longest observation period into account. DR screening was performed through quality assured national screening programs. Multiple logistic regression models adjusted for the year of the eye examination, age, gender, minority status, and duration of T1D were used to evaluate clinical characteristics and the risk of DR. Data from 156,090 in iduals (47.1% female, median age 15.7 years, median duration of diabetes 5.2 years) were included. Overall, the unadjusted prevalence of any DR was 5.8%, varying from 0.0% (0/276) to 16.2% between countries. The probability of DR increased with longer disease duration (aOR The prevalence of DR in this large cohort of youth with T1D varied among countries, increased with diabetes duration, decreased over time, and was associated with higher HbA1c, hypertension, and smoking.
Publisher: IEEE
Date: 09-2015
Publisher: ACM
Date: 19-04-2023
Publisher: IEEE
Date: 08-08-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: IEEE
Date: 10-2017
Publisher: ACM
Date: 13-03-2023
Publisher: IEEE
Date: 12-2016
Publisher: Informa UK Limited
Date: 06-04-2021
Publisher: Elsevier BV
Date: 08-2021
Publisher: Springer International Publishing
Date: 2020
Publisher: Association for Computing Machinery (ACM)
Date: 09-02-2021
DOI: 10.1145/3439720
Abstract: Robotic applications have entered various aspects of our lives, such as health care and educational services. In such Human-robot Interaction (HRI), trust and mutual adaption are established and maintained through a positive social relationship between a user and a robot. This social relationship relies on the perceived competence of a robot on the social-emotional dimension. However, because of technical limitations and user heterogeneity, current HRI is far from error-free, especially when a system leaves controlled lab environments and is applied to in-the-wild conditions. Errors in HRI may either degrade a user’s perception of a robot’s capability in achieving a task (defined as performance errors in this work) or degrade a user’s perception of a robot’s socio-affective competence (defined as social errors in this work). The impact of these errors and effective strategies to handle such an impact remains an open question. We focus on social errors in HRI in this work. In particular, we identify the major attributes of perceived socio-affective competence by reviewing human social interaction studies and HRI error studies. This motivates us to propose a taxonomy of social errors in HRI. We then discuss the impact of social errors situated in three representative HRI scenarios. This article provides foundations for a systematic analysis of the social-emotional dimension of HRI. The proposed taxonomy of social errors encourages the development of user-centered HRI systems, designed to offer positive and adaptive interaction experiences and improved interaction outcomes.
Publisher: IEEE
Date: 08-2020
Publisher: IEEE
Date: 09-2015
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Leimin Tian.