The Challenge
Traditional healthcare systems lacked real-time detection capabilities for aura-related episodes.
Existing AI solutions were not accurate or scalable enough for clinical use.
Ethical and regulatory compliance was not sufficiently addressed in most AI tools.
The Solution
Developed real-time detection using deep learning models.
Built scalable data pipelines for preprocessing and model training.
Leveraged cloud-based frameworks (TensorFlow, PyTorch) for efficient deployment.
Ensured regulatory compliance with ethical AI practices and bias mitigation.
The Result
Achieved higher accuracy and reliability in detecting health episodes.
Enabled timely medical interventions, improving patient outcomes.
Delivered a scalable AI architecture ready for future healthcare applications.
Created a framework for ethical AI, building stakeholder trust and regulatory confidence.
