Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.
COMPLETED
2000 participants
OBSERVATIONAL
2024-08-15
2025-01-30
Brief Summary
Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.
The main questions to be addressed are:
1. Assessing the effectiveness of large language models (LLMs) in the diagnosis and treatment of ophthalmic diseases: Through randomized controlled trials (RCTs), evaluate the diagnostic and treatment effectiveness of LLMs in the field of ophthalmic diseases, exploring their potential to improve the quality and efficiency of ophthalmic care.
2. Investigating the role of LLMs in medical consultations: Explore the role and effectiveness of LLMs in medical consultations for ophthalmic diseases, including their ability to provide medical advice, explain diagnostic results, and help patients understand treatment plans.
3. Examining the ability of LLMs to adhere to ethical standards: Study how to ensure that LLMs comply with ethical standards and moral principles in ophthalmic medical consultations, safeguarding patient privacy and rights.
4. Providing new technological support for the field of ophthalmology: Through research on the application of LLMs in ophthalmic diseases, offer new technological support and innovations to enhance the quality and efficiency of ophthalmic care.
5. Exploring the differences between LLMs and ophthalmologists: By utilizing multiple large language models, compare the differences between LLMs and ophthalmologists in diagnostic outcomes, case analysis processes, and patient experiences during diagnosis and treatment.
6. Evaluating the effectiveness of LLMs in ophthalmic diseases: Collect patient complaints, fundus images, doctors' diagnoses, and diagnosis times from offline doctor consultations, as well as gather AI-generated medical advice, diagnostic efficiency, and diagnostic accuracy online. Ultimately, conduct comprehensive data analysis to determine the feasibility and effectiveness of LLMs in diagnosing and treating ophthalmic diseases.
Related Clinical Trials
Explore similar clinical trials based on study characteristics and research focus.
Glaucoma Screening With Artificial Intelligence
NCT06012058
Glaucoma Screening Using An Artificial Intelligence Assisted Clinical Model in Singapore's Diabetic Eye Screening Program
NCT07243665
Diagnostic Efficacy of CNN in Differentiation of Visual Field
NCT03759483
Artificial Intelligence-assissted Glaucoma Evaluation
NCT03268031
Prevalence of Corneal Astigmatism Before Glaucoma Surgery in Chinese Patients With Primary Angle-closure Glaucoma
NCT03159780
Detailed Description
Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.
Conditions
See the medical conditions and disease areas that this research is targeting or investigating.
Study Design
Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.
OTHER
RETROSPECTIVE
Study Groups
Review each arm or cohort in the study, along with the interventions and objectives associated with them.
Large Language Model Diagnostics Group
GPT-4o mini;Claude 3 Haiku;Gemini 1.5 Flash;Llama 3.1 7OB;GPT-4o;Claude 3.5 Sonnet;Gemini 1.5 Pro;Llama 3.1 4O5B
Input all the patient's information into the large language model and process it using a pre-defined prompt.
Large Language Model Medical Assistance Group
GPT-4o mini;Claude 3 Haiku;Gemini 1.5 Flash;Llama 3.1 7OB;GPT-4o;Claude 3.5 Sonnet;Gemini 1.5 Pro;Llama 3.1 4O5B
Input all the patient's information into the large language model and process it using a pre-defined prompt.
Large Language Model Medical Explanation Team
GPT-4o mini;Claude 3 Haiku;Gemini 1.5 Flash;Llama 3.1 7OB;GPT-4o;Claude 3.5 Sonnet;Gemini 1.5 Pro;Llama 3.1 4O5B
Input all the patient's information into the large language model and process it using a pre-defined prompt.
Interventions
Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.
GPT-4o mini;Claude 3 Haiku;Gemini 1.5 Flash;Llama 3.1 7OB;GPT-4o;Claude 3.5 Sonnet;Gemini 1.5 Pro;Llama 3.1 4O5B
Input all the patient's information into the large language model and process it using a pre-defined prompt.
Eligibility Criteria
Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.
Inclusion Criteria
Exclusion Criteria
ALL
No
Sponsors
Meet the organizations funding or collaborating on the study and learn about their roles.
Affiliated Hospital of North Sichuan Medical College
OTHER
North Sichuan Medical College
OTHER
Responsible Party
Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.
Zining Luo
Principal Investigator
Locations
Explore where the study is taking place and check the recruitment status at each participating site.
Affiliated Hospital of North Sichuan Medical College
Nanchong, Sichuan, China
Countries
Review the countries where the study has at least one active or historical site.
Other Identifiers
Review additional registry numbers or institutional identifiers associated with this trial.
2765326471-2024-1
Identifier Type: -
Identifier Source: org_study_id
More Related Trials
Additional clinical trials that may be relevant based on similarity analysis.