AIMC Topic: Surveys and Questionnaires

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Machine learning-based discrimination of unipolar depression and bipolar disorder with streamlined shortlist in adolescents of different ages.

Computers in biology and medicine
BACKGROUND: Variations in symptoms and indistinguishable depression episodes of unipolar depression (UD) and bipolar disorder (BD) make the discrimination difficult and time-consuming. For adolescents with high disease prevalence, an efficient diagno...

AI implementation: Radiologists' perspectives on AI-enabled opportunistic CT screening.

Clinical imaging
OBJECTIVE: AI adoption requires perceived value by end-users. AI-enabled opportunistic CT screening (OS) detects incidental clinically meaningful imaging risk markers on CT for potential preventative health benefit. This investigation assesses radiol...

Sentiment of Nurses Towards Artificial Intelligence and Resistance to Change in Healthcare Organisations: A Mixed-Method Study.

Journal of advanced nursing
BACKGROUND: Research identified preliminary evidence that artificial intelligence (AI) has emerged as a transformative force in healthcare, revolutionising various aspects of healthcare delivery, from diagnostics to treatment planning. However, integ...

Risk factors for depression in China based on machine learning algorithms: A cross-sectional survey of 264,557 non-manual workers.

Journal of affective disorders
BACKGROUND: Factors related to depression differ depending on the population studied, and studies focusing on the population of non-manual workers are lacking. Thus, we aimed to identify the risk factors related to depression in non-manual workers in...

Addressing pollution challenges for enterprises under diverse extreme climate conditions: artificial intelligence-driven experience and policy support of top Chinese enterprises.

Frontiers in public health
INTRODUCTION: This study investigates the experiences of leading Chinese companies in environmental conservation under varying extreme climate conditions, focusing on the role of artificial intelligence (AI) and governmental assistance.

Students' perception of the use of artificial intelligence (AI) in pharmacy school.

Currents in pharmacy teaching & learning
INTRODUCTION: The increasing adoption of artificial intelligence (AI) among college students, particularly in pharmacy education, raises ethical concerns and prompts debates on responsible usage. The promise of the potential to reduce workload is met...

Constructing a Hospital Department Development-Level Assessment Model: Machine Learning and Expert Consultation Approach in Complex Hospital Data Environments.

JMIR formative research
BACKGROUND: Every hospital manager aims to build harmonious, mutually beneficial, and steady-state departments. Therefore, it is important to explore a hospital department development assessment model based on objective hospital data.

Use and understanding of AI in the ART laboratory: an international survey.

Reproductive biomedicine online
RESEARCH QUESTION: What is the awareness, adoption and comprehension of artificial intelligence (AI) among assisted reproductive technology (ART) laboratory professionals?

Encompassing trust in medical AI from the perspective of medical students: a quantitative comparative study.

BMC medical ethics
BACKGROUND: In the years to come, artificial intelligence will become an indispensable tool in medical practice. The digital transformation will undoubtedly affect today's medical students. This study focuses on trust from the perspective of three gr...

Deep learning for the harmonization of structural MRI scans: a survey.

Biomedical engineering online
Medical imaging datasets for research are frequently collected from multiple imaging centers using different scanners, protocols, and settings. These variations affect data consistency and compatibility across different sources. Image harmonization i...