Related Experiment Video
Updated: Apr 10, 2026
Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli
Published on: April 5, 2019
New horizons in artificial intelligence-assisted pain management: Evaluation of Gemini performance in the older
1Selcuk University, Nursing Department, Turkey.
Aim:
To reveal the potential of artificial intelligence-based educational applications in increasing the knowledge level and application skills of older adults individuals on pain management.
Materials And Methods:
Specific questions were prepared based on guidelines on common pain management in the older adults. These questions were divided into three themes: general information, management techniques (AI-assisted), and clinical scenarios. Questions were entered into the Gemini 3.0 (thinking) feature. The answers were evaluated by two experienced expert nurses in terms of scientific accuracy, scientific quality, and understandability. The practical applicability of the answers was evaluated by a geriatric specialist.
Findings:
In expert evaluations, the vast majority of AI answers were found to be scientifically correct, but disagreements were observed among experts on some questions. The scientific quality of the answers was found to be close to perfect. The average level of understandability of the answers was measured as close to 'very understandable' and the average level of practical applicability was measured as close to 'very applicable'.
Conclusion:
Gemini 3.0 (thinking) AI model has the potential to produce answers that demonstrate a high level of scientific accuracy, understandability and applicability in the management of common pain in the older adults. In particular, the use of the "thinking" feature contributed to the evidence-based and consistent answers. AI can be a valuable support tool for healthcare professionals in clinical decision-making processes.
