SymptoAI

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  first page ui desine

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  use ml.net for prediction

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  give the prediction disease in 3 option and asked the any other symptom .

Inspiration

In our world, many people face serious health challenges. Many fall ill without knowing the exact name of their disease. Some suffer from multiple illnesses without proper diagnosis. Unfortunately, some individuals cannot afford the necessary medication, which can lead to severe consequences, including death. Our AI system aims to help these people by providing quick, accurate disease predictions and guiding them toward appropriate treatments, making healthcare more accessible and saving lives.

What it does

Many people around the world get sick but don’t always know what illness they have because they can’t get proper medical tests or diagnosis. Some have multiple health problems but don’t know the exact diseases they are facing. Also, some people can’t afford medicines or treatment, which makes their situation worse and sometimes leads to death.

Your AI system helps by letting users select their symptoms, then it predicts possible diseases quickly and asks follow-up questions to improve accuracy. This can help users understand their health problems better and get advice on treatment — even if they don’t have easy access to doctors or hospitals. So, your system can potentially save lives by making diagnosis and treatment information more accessible.

How we built it

It is built using ML.NET and the C# programming language. I created my own dataset and trained a multi-classification model. Additionally, I designed the user interface using XML.

Challenges we ran into

While creating this system, I encountered several challenges. One of the major difficulties was collecting accurate and relevant data to build a reliable dataset. Designing the user interface also presented challenges, especially when working with layouts in XML. Additionally, I faced performance issues on my laptop, which would sometimes freeze or become unresponsive when handling large tasks like training the model or rendering complex UI components.

Accomplishments that we're proud of

Successfully built an AI system capable of predicting multiple diseases based on user-selected symptoms. Created a custom dataset from scratch and trained a multi-classification model using ML.NET. Designed a user-friendly interface using XML for easy symptom selection and interactive diagnosis. Integrated follow-up questioning and refinement logic to improve prediction accuracy. Developed a solution that can assist people who lack access to proper healthcare or cannot afford treatment. Overcame technical challenges related to dataset handling, UI design, and hardware limitations.

What we learned

How to identify real-world problems and think creatively to design unique solutions. Gained hands-on experience with machine learning and how machines can learn from data to make predictions. Understood the logic behind machine learning models, especially multi-class classification using ML.NET. Learned how to connect AI with user interaction through a well-designed interface. Developed a deeper appreciation for how technology can be used to help people in need.

What's next for SymptoAI

Add voice input for symptoms Include more diseases and symptoms in the dataset Integrate real-time health monitoring devices Enhance UI for better user experience

Built With

• csharp
• ml.net
• xml