AIMC Topic: Surveys and Questionnaires

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Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

Journal of diabetes research
BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas...

[Acceptance of assistive robots in the field of nursing and healthcare : Representative data show a clear picture for Germany].

Zeitschrift fur Gerontologie und Geriatrie
In view of the ageing society and the high costs of support and care in private households, the question arises as to what role assistive robots can play. This article focuses on the extent to which robots in nursing are accepted by the adult populat...

Fuzzy logic programming and adaptable design of medical products for the COVID-19 anti-epidemic normalization.

Computer methods and programs in biomedicine
BACKGROUND: The COVID-19 prevention and control constantly affects lives worldwide. In this paper, household medical products were analyzed using fuzzy logic. Considering the household anti-epidemic status, economic and environmental benefits, the ad...

Using Machine Learning to Generate Novel Hypotheses: Increasing Optimism About COVID-19 Makes People Less Willing to Justify Unethical Behaviors.

Psychological science
How can we nudge people to not engage in unethical behaviors, such as hoarding and violating social-distancing guidelines, during the COVID-19 pandemic? Because past research on antecedents of unethical behavior has not provided a clear answer, we tu...

Users with spinal cord injury experience of robotic Locomotor exoskeletons: a qualitative study of the benefits, limitations, and recommendations.

Journal of neuroengineering and rehabilitation
BACKGROUND: Persons with spinal cord injury (SCI) may experience both psychological and physiological benefits from robotic locomotor exoskeleton use, and knowledgeable users may have valuable perspectives to inform future development. The objective ...

Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study.

Journal of medical Internet research
BACKGROUND: Early detection of melanoma can be lifesaving but this remains a challenge. Recent diagnostic studies have revealed the superiority of artificial intelligence (AI) in classifying dermoscopic images of melanoma and nevi, concluding that th...

Attitudes and perceptions of dental students towards artificial intelligence.

Journal of dental education
INTRODUCTION: Artificial Intelligence (AI) is a burning topic and use of AI in our day-to-day life has increased exponentially. The purpose of this study was to evaluate the attitudes and perceptions of Turkish dental students towards AI and to provi...

Machine learning-based automated classification of headache disorders using patient-reported questionnaires.

Scientific reports
Classification of headache disorders is dependent on a subjective self-report from patients and its interpretation by physicians. We aimed to apply objective data-driven machine learning approaches to analyze patient-reported symptoms and test the fe...

Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings.

BMC medical informatics and decision making
BACKGROUND: Despite the vagueness and uncertainty that is intrinsic in any medical act, interpretation and decision (including acts of data reporting and representation of relevant medical conditions), still little research has focused on how to expl...