The problem VedyA - Simplifying Health solves

VedyA is a cutting-edge healthcare project designed to transform how individuals access medical information and services. It uses Machine Learning Algorithms and Models to detect the type of disease that a person might have based on the symptoms. It takes the input as the symptoms that one is facing and detects the disease and depectits the diseases. The dataset for now can detect 132 diseases. The accuracy of this model is 100%. It is a comprehensive platform that connects patients with healthcare providers and fosters a vibrant healthcare community.

1. VedyA provides a user-friendly platform for individuals to input their symptoms, leveraging advanced Machine Learning algorithms to accurately detect potential diseases. This enables better access to medical information, empowering users to understand their health concerns.
2. Finding the right doctor or healthcare provider can be a complex and time-consuming process. VedyA simplifies this by connecting patients with relevant healthcare professionals, streamlining the process of seeking medical assistance.
3. VedyA also gives Hospitals reviews in order to promote transperancy and give the user information about the past experience there.
4. VedyA fosters a healthcare community where users can engage in discussions, seek advice, and interact with medical professionals. This alleviates the issue of fragmented healthcare information by creating a platform for shared knowledge and support.
5. VedyA will offer real-time updates on hospital bed availability, promoting resource efficiency, particularly during crucial healthcare situations.(Future Scope)
6. If any patient is unable to describe their issue, We wish to create inter-architectal array quiz which will help them determine the disease and symptoms. Implementing camera and microphone helping user to describe their issues.

Challenges we ran into

Developing accurate Machine Learning algorithms for disease detection is complex and requires extensive training and testing to achieve high accuracy.
Convincing both healthcare providers and patients to adopt the platform can be a challenge. It requires effective marketing and building trust in the system's accuracy and security.
As the platform grows, managing a large user base and data volume becomes a significant challenge. Scalability must be built into the system's architecture.
Developing and maintaining a user-friendly web application with real-time updates, push notifications, and data management can be technically challenging.
Adhering to healthcare regulations, data protection laws, and industry standards is essential. Ensuring compliance adds complexity to the development process.