GeneScan Pro

A non-diagnostic educational app that simulates blood analysis, visualizing cells and genes in real time. It highlights abnormal patterns with a smart algorithm, turning biology into direct learning.

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Inspiration

Our inspiration for GeneScan Pro comes from an interest in the field of bioinformatics. Our team has carefully researched healthcare design standards, and patient needs to understand the field and the needs required for this app. This app is mainly used to detect early diseases that you think you might have. Did you know that almost 2 billion people, almost all of these global death tolls, come from misinterpreted low blood reports indicated by these incorrect results. We have developed a custom algorithm to detect issues and cell abnormalities in the blood sample. We have created this platform for people to detect disease before it reaches a late stage of the disease or any other dangerous illness. This is a warning that can be used for people around the world. We have also sourced the data from trusted organizations to ensure it is as accurate as possible. This project really motivated us to create a user-friendly platform that is both innovative and helpful to people around the world. It helps people gain real information and also learn how to improve healthcare websites for everyone who needs it.

What it does

It is a website that detects early cell anomalies and cell abnormalities to aid in the early detection of a disease using a blood sample.

How we built it

We built it using the Gemini 3 API and Google AI Studio, along with key frameworks that enhance the app's overall functionality and cohesion. The Gemini 3 API does a lot of things in the overall framework of the website. The website has its AI Lab Assistant, aided by Gemini, and also includes a cell imaging visualization center, which is the website's key feature.

Challenges we ran into

Some challenges we ran into are developing the custom cell algorithm, loading the pre-loaded blood samples to analyze, and also having trouble with the cell imaging or cell visualization area.

Accomplishments that we're proud of

The accomplishments that we're proud of are the custom algorithm that was built and the professional cell visualization area we have built.

What we learned

We learned a lot of key terms and cell imaging tools, and vocabulary while being interested and gaining new knowledge in the field of bioinformatics.

What's next for GeneScan Pro

The next process for GeneScan Pro is to use Machine Learning Algorithms to train it more to become more accurate so it can be used in the real world.

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