The tool provides accurate and fast analysis, which can significantly improve the efficiency of ophthalmological diagnostics. By reducing the time required to evaluate each case and increasing the accuracy of diagnoses, RetinAI OCT Expert provides crucial support in clinical decision-making, enabling faster interventions and more effective treatments for patients. Furthermore, the AI’s ability to learn from large volumes of data allows the system to continuously improve, increasing its accuracy and usefulness over time.
No, the artificial intelligence of RetinAI OCT Expert should in no way be a substitute for medical evaluation.
The doctor's interaction with the results generated by AI is crucial, as it considers the patient's clinical context and other relevant factors that AI cannot evaluate. Therefore, the technology aims to increase the efficiency and accuracy of diagnoses, but it should not be viewed in isolation, without medical evaluation.
RetinAI OCT Expert uses advanced AI algorithms with frameworks such as TensorFlow and PyTorch , trained on renowned databases such as EyePACS and Kaggle Diabetic Retinopathy , combined with custom in-house data. This robust training enables the system to identify structural changes in the retina and vitreous with extreme accuracy, classifying conditions such as Age-Related Macular Degeneration (AMD) , Diabetic Retinopathy , and Macular Edema . Additionally, its automated retinal layer segmentation technology minimizes human error and provides consistent and reliable real-time analysis.
Yes! RetinAI OCT Expert is designed to be broadly compatible with leading OCT equipment manufacturers and clinical management systems (EMR). It accepts images in a variety of formats and performs automated integration with electronic medical records, streamlining the workflow in the clinic. In addition, the system offers secure cloud storage for compliments and images, ensuring quick access and efficient sharing. These features make RetinAI an ideal solution for clinics and hospitals of any size.
Report generation in RetinAI is fully automated and follows international ophthalmology standards. After uploading the OCT image, the system analyzes the data, segments the retinal layers and identifies pathological changes. The generated report includes:
Detailed description of blocked changes.
Images annotated with areas of interest.
Illustrative graphs of the analysis.
Clinical recommendations based on ophthalmology guidelines. Reports can be customized with your clinic logo and are ready for printing or digital sharing. This functionality saves time and improves efficiency in patient care.
Yes, RetinAI OCT Expert was developed with a strong commitment to security and legal compliance. The entire system is designed to meet the requirements of major global medical data protection regulations, including:
LGPD (Brazil): Ensure that patient data is treated with transparency and security.
GDPR (Europe): Provides advanced protection against misuse of personal data.
HIPAA (USA): Ensures the confidentiality and integrity of health information. The platform uses end-to-end encryption to protect data during transmission, processing, and storage, and provides secure access options for authorized users.
RetinAI OCT Expert automates crucial steps in the diagnostic process, allowing clinicians and staff to focus on patient care. Here are the key ways to streamline your workflow:
Fast and automated analyses: Diagnoses in just a few seconds, reducing the time required to interpret exams.
Customized, ready-to-use reports: Complete reports are generated automatically, eliminating the need for manual transcription.
Seamless integration with existing systems: Compatible with OCT equipment and electronic medical record systems, ensuring that all information is centralized. This automation not only increases staff productivity, but also improves the patient experience by delivering fast and accurate results.
Yes, RetinAI OCT Expert is equipped with features that allow not only the detection of pathologies, but also the monitoring of their evolution over time.
Comparative Analysis: The system can compare previous and current scans, identifying progressions or regressions of conditions such as AMD, macular edema and diabetic retinopathy.
Trend Graphs: Visualizations provided help clinicians understand changes in retinal thickness and other relevant considerations.
Progression Alerts: Automatically identifies significant changes that may require immediate clinical intervention. This functionality makes RetinAI an indispensable tool for managing chronic eye diseases.
RetinAI OCT Expert is designed to empower clinicians to deliver more personalized and effective care. Here’s how it makes it easier:
Detailed and Specific Reports: Each report is tailored based on the patient's individual findings, highlighting relevant changes and personalized recommendations.
Individual Progression Monitoring: The system allows the comparison of exams from the same patient, identifying specific changes that help adapt the treatment plan.
Ease of Patient Communication: Clear, visually rich reports can be shared directly with patients, increasing understanding and adherence to treatment. With RetinAI, clinicians not only gain efficiency, but also improve the quality of care by ensuring that every decision is informed by the most accurate and relevant data.
The development of RetinAI OCT Expert has advanced a meticulous process of scientific and technological validation, in compliance with the most rigorous international standards. The platform was created with the goal of providing clinical accuracy, safety and reliability for ophthalmologists. Below is a breakdown of the validation process and the centers involved:
Scientific and Technological Validation Process
The development and validation pipeline has progressed through these critical steps:
Data Selection and Preparation for AI Training:
Retina Experts: Initial data curation was performed by experts, ensuring that the images used were of high quality and clinically relevant.
Data Sources: Data were extracted from reference databases, such as EyePACS and Kaggle Diabetic Retinopathy, combined with exclusive internal databases for greater personalization and clinical applicability.
Data Annotation by Experts:
The images were detailed annotated by experienced ophthalmologists using specific tools for specific pathologies, retinal layers and other relevant features.
Quality Assurance in Notes:
Strict supervision was carried out by a retina-specialized QA (Quality Assurance) team, ensuring that annotations were accurate and error-free.
Approval for AI Training Experiments:
After validating the annotations, the dataset was approved by an expert supervisor to be used in artificial intelligence models.
Model Training and Tuning:
Frameworks Used: Training was performed with TensorFlow and PyTorch, frameworks recognized for their robustness in deep learning.
MONAI: Tool optimized for medical applications such as OCT image segmentation.
Continuous Testing and Iteration:
Training models were tested on real patient data and clinical conditions to adjust ranges and maximize accuracy.
Automated Reports:
The system has been configured to generate automated reports that meet international quality standards.
Compliance with International Regulations
RetinAI OCT Expert has been developed in compliance with the highest quality standards, medical regulations and data protection laws, including:
EU AI ACT: Complies with European regulations on artificial intelligence to ensure safety and transparency.
GDPR: Protects sensitive data in compliance with European privacy regulations.
ISO 13485: International certification for quality management systems for medical devices.
CE (Conformité Européenne): Meets the standards required for medical devices marketed in the European Union.
FDA Clearance: Approval for use in the United States, reinforcing safety and efficacy.
HIPAA Compliance: Ensure compliance with US healthcare data privacy legislation.
Scientific Centers and Collaborations
The development of RetinAI involves partnerships with leading ophthalmology research centers and globally recognized academic institutions. Some of the key highlights include:
RetinaAI Study Center: Focused on the use of artificial intelligence applied to ophthalmology.
Prestigious Universities: Academic institutions built on independent data and evaluations.
International Reference Hospitals: Clinical validations were carried out in large hospitals, allowing adjustments in real usage scenarios.