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About the Project

Inspiration Cardiovascular diseases are a major global health concern, and understanding heart disease risk can be difficult for many people. We were inspired to build Sellution, a platform that makes cardiovascular risk easier to understand through interactive and engaging visualizations.

What We Built We developed an interactive cardiovascular risk visualization platform that transforms health-related information into clear visual insights. Our goal is to make complex health data more accessible, improve awareness of potential risk factors, and encourage people to take a proactive approach to heart health.

How We Built It We designed a web-based interface focused on interactive visualizations and user-friendly presentation. The project combines cardiovascular risk concepts with visual elements to help users explore and better understand heart health information.

Challenges We Faced One of our main challenges was presenting complex cardiovascular information in a simple, intuitive, and visually appealing way. We also focused on making the interface engaging and easy to navigate while ensuring the visualizations communicate information clearly.

What We Learned Through this project, we learned the importance of user-centered design, effective data visualization, and simplifying complex health information. We also gained experience in developing interactive web applications and understanding how technology can support health awareness.

Future Scope We aim to enhance CardioVision 3D with more comprehensive risk assessment features, personalized insights, and improved visual analytics. Our long-term vision is to make cardiovascular health information more understandable and accessible, supporting awareness and preventive healthcare.

Our mission is simple: turn complex cardiovascular data into clear visual insights that empower people to understand and care for their heart health.

Built With

3d
analytics
artificial
cardiovascular
css
data
development
health
healthcare
healthtech
intelligence
javascript
machine
medical
predictive
preventive
python
react
technology
visualization
web

Submitted to

Multimodal AI Hackathon 2026

Created by

Omm priyanshu Pati— AI/ML Engineer
Machine Learning
- Collect and preprocess the heart-disease dataset.
- Train and compare ML models.
- Evaluate performance using accuracy, precision, recall, F1-score and other appropriate metrics.
- Save the trained model and build the prediction API.
- Implement model explanations and document limitations.
Deliverable: trained model, evaluation report and working prediction endpoint.

Shr Swasat Das — Frontend & 3D Developer
UI/UX and Visualization
- Build the responsive web dashboard based on the reference designs.
- Develop the interactive 3D heart or human anatomical viewer.
- Implement rotation, zoom, anatomical selection and contextual panels.
- Create patient input forms, result cards and charts.
- Connect the frontend to the prediction API.
Deliverable: complete user interface and interactive 3D visualization.

Saswata Pattanaik — Backend, Integration & Deployment Engineer
Backend and QA
- Set up the backend and API contracts.
- Integrate the trained model with the frontend.
- Implement input validation, error handling and model loading.
- Test the complete prediction workflow.
- Handle deployment, environment configuration and technical documentation.
Deliverable: integrated, tested and deployable application.

Omm priyanshu pati
Saswata Pattanaik
Sri Saswat Das

Updates

Omm priyanshu pati started this project — Oct 14, 2026 02:06 PM EDT

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