AIMC Topic: Self Report

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Emotional impact of AI-generated vs. human-composed music in audiovisual media: A biometric and self-report study.

PloS one
Generative artificial intelligence (AI) has evolved rapidly, sparking debates about its impact on the visual and sonic arts. Despite its growing integration into creative industries, public opinion remains sceptical, viewing creativity as uniquely hu...

Characterising physical activity patterns in community-dwelling older adults using digital phenotyping: a 2-week observational study protocol.

BMJ open
INTRODUCTION: Physical activity (PA) is crucial for older adults' well-being and mitigating health risks. Encouraging active lifestyles requires a deeper understanding of the factors influencing PA, which conventional approaches often overlook by ass...

Changes in recreational drug use, reasons for those changes and their consequence during and after the COVID-19 pandemic in the UK.

Comprehensive psychiatry
Changes in drug use in the general population during the COVID-19 pandemic and their long-term consequences are not well understood. We employed natural language processing and machine learning to analyse a large dataset of self-reported rates of and...

AI-Powered Analysis of Weight Loss Reports from Reddit: Unlocking Social Media's Potential in Dietary Assessment.

Nutrients
: The increasing use of social media for sharing health and diet experiences presents new opportunities for nutritional research and dietary assessment. Large language models (LLMs) and artificial intelligence (AI) offer innovative approaches to anal...

Exploring the importance of clinical and sociodemographic factors on self-rated health in midlife: A cross-sectional study using machine learning.

International journal of medical informatics
BACKGROUND: Self-rated health (SRH) is influenced by various factors, including clinical and sociodemographic characteristics. However, in the context of Brazil, we still lack a clear understanding of the relative importance of these factors and how ...

Detecting noncredible symptomology in ADHD evaluations using machine learning.

Journal of clinical and experimental neuropsychology
INTRODUCTION: Diagnostic evaluations for attention-deficit/hyperactivity disorder (ADHD) are becoming increasingly complicated by the number of adults who fabricate or exaggerate symptoms. Novel methods are needed to improve the assessment process re...

Machine learning in the prediction of human wellbeing.

Scientific reports
Subjective wellbeing data are increasingly used across the social sciences. Yet, despite the widespread use of such data, the predictive power of approaches commonly used to model wellbeing is only limited. In response, we here use tree-based Machine...

The role of psychological factors in predicting self-rated health: implications from machine learning models.

Psychology, health & medicine
Self-rated health (SRH) is a significant predictor of future health outcomes. Despite the contribution of psychological factors in individuals' subjective health assessments, prior studies of machine learning-based prediction models primarily focused...

Development and validation of a new nomogram for self-reported OA based on machine learning: a cross-sectional study.

Scientific reports
Developing a new diagnostic prediction model for osteoarthritis (OA) to assess the likelihood of individuals developing OA is crucial for the timely identification of potential populations of OA. This allows for further diagnosis and intervention, wh...

SymScore: Machine learning accuracy meets transparency in a symbolic regression-based clinical score generator.

Computers in biology and medicine
Self-report questionnaires play a crucial role in healthcare for assessing disease risks, yet their extensive length can be burdensome for respondents, potentially compromising data quality. To address this, machine learning-based shortened questionn...