AIMC Topic: Surveys and Questionnaires

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Taking the plunge together: A student-led faculty learning seminar series on artificial intelligence.

Currents in pharmacy teaching & learning
OBJECTIVE: This pilot study explored the effectiveness of a student-led faculty development series by evaluating two key outcomes: the capacity of students to deliver meaningful professional development sessions to faculty and the impact of these ses...

Fostering creativity-nurturing behaviors among nurse educators: Investigating the interplay between evidence-based practice climate and artificial intelligence competence self-efficacy.

Nurse education today
BACKGROUND: Fostering creativity in nursing education is essential for equipping students with critical thinking and problem-solving skills. Nurse educators play a pivotal role in nurturing creativity among nursing students, yet their effectiveness i...

Investigation of the relationship between medical artificial intelligence readiness and individual innovativeness levels in nursing students.

Nurse education today
AIM: This study was conducted to identify nursing students' medical artificial intelligence readiness and individual innovativeness levels, to examine the relationship between these two concepts and to determine the variables that create a significan...

Evaluation of Chatbots in the Emergency Management of Avulsion Injuries.

Dental traumatology : official publication of International Association for Dental Traumatology
BACKGROUND: This study assessed the accuracy and consistency of responses provided by six Artificial Intelligence (AI) applications, ChatGPT version 3.5 (OpenAI), ChatGPT version 4 (OpenAI), ChatGPT version 4.0 (OpenAI), Perplexity (Perplexity.AI), G...

IPEM topical report: results of a 2024 UK survey of artificial intelligence in medical physics and clinical engineering.

Physics in medicine and biology
Medical physics and clinical engineering (MPCE) professionals have a critical role in the safe and effective deployment of artificial intelligence (AI) in healthcare, however their attitudes and opinions towards AI are not well understood. A 2024 sur...

Comparative Analysis of Large Language Models for Answering Cancer-Related Questions in Korean.

Yonsei medical journal
PURPOSE: Large language models (LLMs) have shown potential in medicine, transforming patient education, clinical decision support, and medical research. However, the effectiveness of LLMs in providing accurate medical information, particularly in non...

Data-driven multi-hazard susceptibility and community perceptions assessment using a mixed-methods approach.

Journal of environmental management
Assessing multi-hazard susceptibility and understanding community insights are important for effective disaster risk management; however, limited research has been conducted to study these aspects together. This study uses a data-driven approach to a...

Approach or avoidance? Relationship between perceived AI explainability and employee job crafting.

Acta psychologica
Amid growing concerns about the lack of transparency in algorithms, heightened focus has been placed on artificial intelligence (AI) explainability in workplace decision-making processes. This study leverages work design theory to explore when and ho...

A general survey on medical image super-resolution via deep learning.

Computers in biology and medicine
Medical image super-resolution (SR) is a classic regression task in low-level vision. Limited by hardware limitations, acquisition time, low radiation dose, and other factors, the spatial resolution of some medical images is not sufficient. To addres...

AI-driven simplification of surgical reports in gynecologic oncology: A potential tool for patient education.

Acta obstetricia et gynecologica Scandinavica
INTRODUCTION: The emergence of large language models heralds a new chapter in natural language processing, with immense potential for improving medical care and especially medical oncology. One recent and publicly available example is Generative Pret...