Reportify

Inspiration

The inspiration behind Reportify comes from a personal experience. A close relative faced a misdiagnosis that had serious consequences. Their platelet count dropped significantly, and doctors, lacking comprehensive patient data, prescribed steroids that caused adverse effects. It was later revealed that the diagnosis was incorrect. This experience opened our eyes to the challenges faced by healthcare professionals who often deal with fragmented data, which can lead to critical errors and delays in patient care. We wanted to create a solution that centralizes patient data, offers AI-powered insights, and ultimately helps doctors make more informed decisions quickly.

What it does

Reportify is a patient management dashboard that centralizes all essential medical data, including previous prescriptions, dosages, and diagnostic X-ray scans. It leverages AI to assist with X-ray analysis, providing quick insights and probabilities for conditions like pneumothorax. The platform also tracks medication history, alerts doctors to potential conflicts, and offers visualizations of key health indicators over time, allowing healthcare professionals to provide better, more accurate care.

How we built it

We built Reportify using a combination of technologies:

• Frontend and Backend: Streamlit for the user interface, data visualization.
• AI Model: We integrated a DenseNet121 model for X-ray classification between 13 diseases and used Llama 3.2 for summarizing blood reports and medicines.
• Data Visualization: Matplotlib for plotting health metrics like platelet counts and hemoglobin levels over time.

The project also includes a file upload feature for adding blood reports and X-rays, with real-time analysis provided by the AI model.

Challenges we ran into

One of the major challenges we faced was fine-tuning the AI model for accurate X-ray diagnosis. Ensuring the model was both fast and reliable in providing medical insights was critical. Another challenge was ensuring the dashboard provided intuitive data visualizations that doctors could interpret quickly during a diagnosis.

Accomplishments that we're proud of

We’re proud of several key accomplishments:

• Successfully integrating AI-driven X-ray analysis to provide real-time diagnostic support.
• Building a user-friendly dashboard that allows doctors to visualize patient data over time.
• Developing a recommendation engine that tracks medications and offers suggestions on ideal prescriptions and dosages.

What we learned

Throughout this project, we learned a lot about the complexities of healthcare data management and the importance of seamless integration between different types of medical information. We also gained deeper insights into building AI models for real-time analysis and how critical proper data visualization is in helping healthcare professionals make quick, informed decisions.

What's next for Reportify

The next steps for Reportify include:

• Expanding the AI diagnostic capabilities to cover more medical conditions and imaging types.
• Integrating with existing Electronic Health Record (EHR) systems to offer a seamless experience for healthcare providers.
• Exploring partnerships with healthcare institutions to pilot Reportify in real-world clinical settings.
• Further enhancing the recommendation engine to personalize treatment plans based on patient history and current health data.

Built With

• streamlit