Ignite Creation Date:
2024-10-26 @ 3:40 PM
Last Modification Date:
2024-10-26 @ 3:40 PM
Study NCT ID:
NCT06607822
Status:
NOT_YET_RECRUITING
Last Update Posted:
None
First Post:
2024-09-11
Brief Title:
Development and Validation of a Large Language Model-based Myopia Assistant System
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Development and Validation of a Large Language Model-based Myopia Assistant System
Status:
NOT_YET_RECRUITING
Status Verified Date:
2024-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Myopia is a rapidly growing global health concern and there is an urgent need for advanced tools that can facilitate personalized healthcare strategies Artificial intelligence AI-based solutions such as large language models offer robust tools for ophthalmic healthcare In this study investigators aim to validate a patient-centered Large Language Model LLM-based Myopia Assistant System with the following key objectives 1 evaluate the ability of the LLM models to generate high-level reports and help self-evaluation of myopia for patients in primary care 2 evaluate its performance in answering evidence-based medicine-oriented questions and improving overall satisfaction within clinics for myopic patients
Detailed Description:
Myopia is a rapidly growing global health concern particularly affecting children and adolescents The progression of myopia can lead to severe complications such as myopic macular degeneration significantly impacting visual acuity and quality of life With the rising prevalence of myopia there is an urgent need for advanced tools that can facilitate personalized healthcare strategies Artificial intelligence AI-based solutions such as large language models offer robust tools for ophthalmic healthcare Nevertheless their effectiveness and safety in real clinical environments have not been fully explored
In this study investigators aim to validate a patient-centered Large Language Model LLM-based Myopia Assistant System with the following key objectives 1 evaluate the ability of the LLM models to generate high-level reports and help self-evaluation of myopia for patients in primary care 2 evaluate its performance in answering evidence-based medicine-oriented questions and improving overall satisfaction within clinics for myopic patients The findings of this study will provide valuable insights for the application of the GPT model in the healthcare field making a significant contribution to improving the accessibility and quality of medical services
In this study investigators aim to validate a patient-centered Large Language Model LLM-based Myopia Assistant System with the following key objectives 1 evaluate the ability of the LLM models to generate high-level reports and help self-evaluation of myopia for patients in primary care 2 evaluate its performance in answering evidence-based medicine-oriented questions and improving overall satisfaction within clinics for myopic patients The findings of this study will provide valuable insights for the application of the GPT model in the healthcare field making a significant contribution to improving the accessibility and quality of medical services
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None