AIMC Topic: Surveys and Questionnaires

Clear Filters Showing 1511 to 1520 of 1624 articles

Clinician Perceptions of Generative Artificial Intelligence Tools and Clinical Workflows: Potential Uses, Motivations for Adoption, and Sentiments on Impact.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Successful integration of Generative Artificial Intelligence (AI) into healthcare requires understanding of health professionals' perspectives, ideally through data-driven approaches. In this study, we use a semi-structured survey and mixed methods a...

A Comparison of LLMs for Use in Generating Synthetic Test Data for Automated Testing of a Patient-Focused, Survey-Based System.

AMIA ... Annual Symposium proceedings. AMIA Symposium
In the context of a patient-focused, survey-based system, we demonstrated the potential of generative AI to create custom synthetic data using 2 different large language models (GPT 3.5 and Flan T5-XL) in AWS and Azure environments. While we improved...

A comparative analysis of GPT-3.5 and GPT-4.0 on a multiple-choice ophthalmology question bank: A study on artificial intelligence developments.

Romanian journal of ophthalmology
INTRODUCTION: To evaluate the performance of ChatGPT-4.0 and ChatGPT-3.5 in answering multiple-choice questions in OphthoQuestions (www.ophthoquestions.com), a popular question preparation bank, and to compare the performance of GPT-4.0 and GPT-3.5.

Comparison of the experience and perception of artificial intelligence among practicing doctors and medical students.

Wiadomosci lekarskie (Warsaw, Poland : 1960)
OBJECTIVE: Aim: To analyze and compare the experiences and perceptions of artificial intelligence (AI) among practicing doctors and medical students.

Evaluation of the reliability and readability of answers given by chatbots to frequently asked questions about endophthalmitis: A cross-sectional study on chatbots.

Health informatics journal
This study aimed to investigate the accuracy, reliability, and readability of A-Eye Consult, ChatGPT-4.0, Google Gemini and Copilot AI large language models (LLMs) in responding to patient questions about endophthalmitis. The LLMs' responses to 25 ...

Identification and Prioritization of Health Indexes in Nomadic Tribespeople by Fuzzy Delphi Method: An Ecological Study.

Inquiry : a journal of medical care organization, provision and financing
The migratory lifestyle of nomadic communities, combined with the lack of a suitable health-related organizational structure, has made it difficult to provide health care services that can improve their health status. To achieve the concept of justic...

Patients' perspectives on the use of artificial intelligence and robots in healthcare.

Bratislavske lekarske listy
OBJECTIVE: We aimed to evaluate the opinions of individuals aged 18 and above in our country regarding the use of artificial intelligence (AI) and robots in the field of healthcare.

New training, new attitudes: non-clinical components in Ukrainian medical PHDs training (regarding critical thinking, academic integrity and artificial intelligence use).

Wiadomosci lekarskie (Warsaw, Poland : 1960)
OBJECTIVE: Aim: The paper studies the attitude to critical thinking, academic integrity and the Artificial Intelligence use of the Ukrainian medical PhD students.

Simplifying Alzheimer's Disease Monitoring: A Novel Machine-Learning Approach to Estimate the Clinical Dementia Rating Sum of Box Changes Using the Mini-Mental State Examination and Functional Activities Questionnaire.

Journal of Alzheimer's disease : JAD
BACKGROUND: Primary outcome measure in the clinical trials of disease modifying therapy (DMT) drugs for Alzheimer's disease (AD) has often been evaluated by Clinical Dementia Rating sum of boxes (CDRSB). However, CDR testing requires specialized trai...

Machine Learning to Identify Clusters in Family Medicine Diplomate Motivations and Their Relationship to Continuing Certification Exam Outcomes: Findings and Potential Future Implications.

Journal of the American Board of Family Medicine : JABFM
BACKGROUND: The potential for machine learning (ML) to enhance the efficiency of medical specialty boards has not been explored. We applied unsupervised ML to identify archetypes among American Board of Family Medicine (ABFM) Diplomates regarding the...