Project Overview
Project Summary:
"BrainProtect" is an AI-based diagnostic system designed to predict and manage the state of cerebral aneurysms. Developed by a team comprising Jung Yongjin, Cho Eunsol, Park Eunbin, Park Chanyun, and Lee Seohyun, the project integrates deep learning technology, health data analysis, and interactive AI to offer early detection and personalized health management strategies for individuals at risk of cerebral aneurysms. It aims to significantly improve outcomes by providing detailed information, predictive analytics, and management solutions to prevent the severe consequences of cerebral aneurysms.
Identifying the Challenge
The Social Problem:
Cerebral aneurysms present a critical health risk due to their high mortality and severe disability rates upon rupture. Early detection is vital as it dramatically increases treatment effectiveness; however, access to screening and diagnostic procedures like MRI and Cerebrovascular angiography is limited and expensive. Additionally, there's a noticeable gap in public awareness and medical infrastructure, especially in less accessible regions, exacerbating the risk of undiagnosed and untreated aneurysms.
Innovation and Uniqueness
Why Our Project Stands Out:
The development of "BrainProtect" has been a profound learning journey for the team. It involved diving deep into the complexities of cerebral aneurysms, understanding the limitations of current diagnostic and management practices, and exploring the potentials of AI and data science in healthcare. The team learned to integrate diverse data sources, including health records and lifestyle information, with advanced AI techniques to develop predictive models. This journey also underscored the importance of interdisciplinary collaboration, as the project brought together expertise from medical research, software engineering, data science, and business administration.
Insights and Development
Learning Journey:
The development of "BrainProtect" has been a profound learning journey for the team. It involved diving deep into the complexities of cerebral aneurysms, understanding the limitations of current diagnostic and management practices, and exploring the potentials of AI and data science in healthcare. The team learned to integrate diverse data sources, including health records and lifestyle information, with advanced AI techniques to develop predictive models. This journey also underscored the importance of interdisciplinary collaboration, as the project brought together expertise from medical research, software engineering, data science, and business administration.
Development Process :
Research and Planning: Identifying the need for early detection of cerebral aneurysms and formulating the project goal.
Data Collection and Analysis: Gathering health data and lifestyle information to analyze risk factors and develop a predictive model using machine learning techniques.
Prototype Development: Designing and creating app prototypes to test the system's functionality, including risk assessment quizzes, health data input methods, and user interface for result presentation.
Testing and Evaluation: Conducting tests to evaluate the predictive accuracy, user experience, and overall performance of the system. The model showed high precision and accuracy in classifying risk levels.
Refinement and Launch: Refining the app based on feedback, improving algorithms, and preparing for a wider launch to make the tool accessible to individuals at risk.
Throughout its development, "BrainProtect" focused on addressing the critical need for early diagnosis and management of cerebral aneurysms, showcasing the potential of AI to revolutionize healthcare accessibility and effectiveness.
