This study aims to compare the clinical value of a general large language model(DeepSeek GPT)and a disease-specific optimized model(BAIMGPT)in pulmonary nodule consultation and management.Through a multicenter real-wo...This study aims to compare the clinical value of a general large language model(DeepSeek GPT)and a disease-specific optimized model(BAIMGPT)in pulmonary nodule consultation and management.Through a multicenter real-world study,1,000 patients with pulmonary nodules from 12 hospitals will be recruited for a randomized self-controlled trial evaluating the performance of the two models across eight dimensions:convenience,friendliness,sense of security,accuracy in question comprehension,response professionalism,voice interaction,visual empowerment,and demand level.The core methodologies include dual user evaluation,third-party blinded review,and endpoint assessment.The study was expected to validate BAIMGPT’s advantages in improving screening awareness,personalized management,and physician-patient trust,providing evidence-based support for AI-powered early lung cancer screening.The protocol has passed ethical review,with anonymized data processing ensuring both innovation and safety.展开更多
ChatGPT,a popular large language model developed by OpenAI,has the potential to transform the management of diabetes mellitus.It is a conversational artificial intelligence model trained on extensive datasets,although...ChatGPT,a popular large language model developed by OpenAI,has the potential to transform the management of diabetes mellitus.It is a conversational artificial intelligence model trained on extensive datasets,although not specifically health-related.The development and core components of ChatGPT include neural networks and machine learning.Since the current model is not yet developed on diabetes-related datasets,it has limitations such as the risk of inaccuracies and the need for human supervision.Nevertheless,it has the potential to aid in patient engagement,medical education,and clinical decision support.In diabetes management,it can contribute to patient education,personalized dietary guidelines,and providing emotional support.Specifically,it is being tested in clinical scenarios such as assessment of obesity,screening for diabetic retinopathy,and provision of guidelines for the management of diabetic ketoacidosis.Ethical and legal considerations are essential before ChatGPT can be integrated into healthcare.Potential concerns relate to data privacy,accuracy of responses,and maintenance of the patient-doctor relationship.Ultimately,while ChatGPT and large language models hold immense potential to revolutionize diabetes care,one needs to weigh their limitations,ethical implications,and the need for human supervision.The integration promises a future of proactive,personalized,and patient-centric care in diabetes management.展开更多
文摘This study aims to compare the clinical value of a general large language model(DeepSeek GPT)and a disease-specific optimized model(BAIMGPT)in pulmonary nodule consultation and management.Through a multicenter real-world study,1,000 patients with pulmonary nodules from 12 hospitals will be recruited for a randomized self-controlled trial evaluating the performance of the two models across eight dimensions:convenience,friendliness,sense of security,accuracy in question comprehension,response professionalism,voice interaction,visual empowerment,and demand level.The core methodologies include dual user evaluation,third-party blinded review,and endpoint assessment.The study was expected to validate BAIMGPT’s advantages in improving screening awareness,personalized management,and physician-patient trust,providing evidence-based support for AI-powered early lung cancer screening.The protocol has passed ethical review,with anonymized data processing ensuring both innovation and safety.
文摘ChatGPT,a popular large language model developed by OpenAI,has the potential to transform the management of diabetes mellitus.It is a conversational artificial intelligence model trained on extensive datasets,although not specifically health-related.The development and core components of ChatGPT include neural networks and machine learning.Since the current model is not yet developed on diabetes-related datasets,it has limitations such as the risk of inaccuracies and the need for human supervision.Nevertheless,it has the potential to aid in patient engagement,medical education,and clinical decision support.In diabetes management,it can contribute to patient education,personalized dietary guidelines,and providing emotional support.Specifically,it is being tested in clinical scenarios such as assessment of obesity,screening for diabetic retinopathy,and provision of guidelines for the management of diabetic ketoacidosis.Ethical and legal considerations are essential before ChatGPT can be integrated into healthcare.Potential concerns relate to data privacy,accuracy of responses,and maintenance of the patient-doctor relationship.Ultimately,while ChatGPT and large language models hold immense potential to revolutionize diabetes care,one needs to weigh their limitations,ethical implications,and the need for human supervision.The integration promises a future of proactive,personalized,and patient-centric care in diabetes management.
