Clinical trial NCT06755190: Ophthalmic Multimodal AI-Assisted Medical Decision-Making
Official title: A Study on Ophthalmic Multimodal AI-Assisted Medical Decision-Making Based on Imaging and Electronic Medical Record Data
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Ocular Diseases
Keywords: ocular diseases
Ophthalmic Multimodal AI-Assisted Medical Decision-Making
Artificial Intelligence
Lead sponsor: The Eye Hospital of Wenzhou Medical University
Sponsor class: OTHER
First posted: 2025-01-01
Enrollment: 5000000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: All patients who have received treatment at multiple centers, including The Eye Hospital of Wenzhou Medical University, First Affiliated Hospital of Wenzhou Medical University, Second Affiliated Hospital of Wenzhou Medical University, ZhuHai Hospital, and Macau University of Science and Technology Hospital.

Brief summary: This is a multi-center, retrospective clinical study designed to evaluate the application and effectiveness of an AI-assisted medical decision support system, leveraging multimodal data fusion, in ophthalmic clinical practice.

Detailed description: Visual impairments significantly affect an individual's quality of life. Early screening, diagnosis, and treatment of ocular diseases are crucial for preventing the onset and progression of vision disorders. In clinical practice, ophthalmologists often need to integrate a wide range of patient data, including demographic information, medical history, biochemical markers such as blood glucose and lipid levels, risk factors, as well as various ophthalmic data, such as fundus images, OCT scans, and visual field tests, to make an accurate diagnosis and develop an appropriate treatment plan. In an era where precision and personalized medicine are at the forefront of healthcare, the early detection and diagnosis of eye diseases, as well as the selection of suitable diagnostic and therapeutic strategies at different stages of the disease, have become significant challenges in clinical settings. Recent advancements in medical imaging and analysis techniques have greatly enhanced the accuracy and effectiveness of ocular disease diagnosis. This study aims to develop an ophthalmic artificial intelligence-assisted decision-making system by integrating multimodal data from imaging and electronic medical records, in combination with deep learning techniques. The objective is to improve diagnostic accuracy, streamline clinical workflows, and provide more personalized treatment options for patients. Ultimately, this system seeks to enhance treatment outcomes and improve the overall quality of life for patients suffering from ocular diseases.

Eligibility criteria: Inclusion Criteria:

1.All patients who have received treatment at multiple centers, including The Eye Hospital of Wenzhou Medical University, First Affiliated Hospital of Wenzhou Medical University, Second Affiliated Hospital of Wenzhou Medical University, ZhuHai Hospital, and Macau University of Science and Technology Hospital.

2.Availability of comprehensive electronic health records (EHR), including: Ophthalmic images (e.g., fundus photography, OCT, or slit-lamp images). Electronic medical records (e.g., diagnosis, treatment, and follow-up notes). Examination results (e.g., visual acuity, intraocular pressure, or laboratory tests). 3.Patients with a clear and confirmed diagnosis of one or more ocular diseases. 4.Patients with sufficient follow-up records to allow assessment of disease progression or prognosis, if applicable.

1. All ophthalmology patients who have previously received treatment at the Department of Ophthalmology, the Eye Hospital of Wenzhou Medical University, First Affiliated Hospital of Wenzhou Medical University, Second Affiliated Hospital of Wenzhou Medical University, Zhuhai People's Hospital, and the University Hospital.
2. Availability of comprehensive electronic health records (EHR), including: Ophthalmic images (e.g., fundus photography, OCT, or slit-lamp images). Electronic medical records (e.g., diagnosis, treatment, and follow-up notes). Examination results (e.g., visual acuity, intraocular pressure, or laboratory tests).
3. Patients with a clear and confirmed diagnosis of one or more ocular diseases.
4. Patients with sufficient follow-up records to allow assessment of disease progression or prognosis, if applicable.

Exclusion Criteria:

1. Incomplete or missing critical EHR components.
2. Cases with ambiguous or unverified diagnoses that cannot be clearly categorized.
3. Duplicated or redundant data from the same patient.

Primary outcomes:
measure: Area Under the Curve (AUC)
timeFrame: 1 years
measure: Sensitivity
timeFrame: 1 years
measure: Accuracy Accuracy Accuracy
timeFrame: 1 years
measure: Specificity
timeFrame: 1 years
measure: False Positive Rate
timeFrame: 1 years
measure: False Negative Rate
timeFrame: 1 years
measure: Postoperative Complication Rate
timeFrame: 1 years
measure: Recurrence Risk Rate
timeFrame: 1 years
measure: Survival Rate
timeFrame: 1 years
measure: Effectiveness of Decision Support
timeFrame: 1 years
measure: Decision Time Efficiency
timeFrame: 1 years
Secondary outcomes:
measure: System Usability Score
timeFrame: 1 years
measure: AI System Response Time
timeFrame: 1 years
measure: System Failure Rate
timeFrame: 1 years
measure: User Interface Design Satisfaction
timeFrame: 1 years
measure: Patient Satisfaction Score
timeFrame: 1 years
measure: Treatment Adherence
timeFrame: 1 years
measure: Physician Acceptance of AI System
timeFrame: 1 years
Other outcomes:
Locations:
city: Zhuhai
country: China
facility: ZhuHai Hospital, zhuhai, guangdong
state: Guangdong
city: Wenzhou
country: China
facility: First Affiliated Hospital of Wenzhou Medical University
state: Zhejiang
city: Wenzhou
country: China
facility: Second Affiliated Hospital of Wenzhou Medical Universit
state: Zhejiang
city: Wenzhou
country: China
facility: The Eye Hospital of Wenzhou Medical University
state: Zhejiang
city: Macau
country: Macau
facility: Macau University of Science and Technology Hospital
Study officials:
affiliation: The Eye Hospital of Wenzhou Medical University
name: Kang Zhang, PhD.
role: PRINCIPAL_INVESTIGATOR
References: