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Precise & InterpretableBrain Tumor Diagnosis

An open-source multimodal AI model to revolutionize neuro-ethics and efficiency in brain tumors

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Published in

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Featured at

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Revolutionizing Life: Frontiers of Biotechnology Conference 2025

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What is Neuroflux?

Neuroflux analyzes MRI scans of brains, classifies the tumor type, and produces a heatmap highlighting tumor damage.

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Visualize

Neuroflux in Action

Slide to reveal how
Neuroflux's heat maps visually pinpoint
tumor regions

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Why Neuroflux Matters

Restorative Yoga

Neuroflux focuses on glioblastoma multiforme, one of the most aggressive brain tumors. Due to vague early symptoms and diagnostic delays, GBM often goes undetected until advanced stages and significantly reduces survival rates.

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Better for Doctors, Better for Patients

Neuroflux accurately identifies brain tumor location and spread, giving doctors clear visual insights for faster decisions. By supporting earlier diagnosis, Neuroflux also helps patients start treatment sooner and improves their chances of recovery.

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SDG 3

Good Health and Well-Being

01

Designed to detect GBM earlier and more accurately, enabling faster diagnosis and improving patient survival outcomes

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Developed as a lightweight, open-source software to ensure access to AI diagnostics for low-resource hospitals without costly computational infrastructure

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Incorporates interpretable heatmaps to empower clinicians in verifying diagnostic decisions, boosting clinical transparency

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Enables radiologists to precisely pinpoint tumor boundaries and plan safer, more effective treatments for patients

Accelerating SDG 3 Targets

Target 3.4: Reduce Premature Mortality

Reducing mortality rates through AI-powered early tumor detection

Target 3.8: Achieve Universal Health Coverage

Expanding access to AI diagnostic tools in underserved regions

What Clinicians &
Researchers are Saying

"This is an outstanding research project conducted by a group of high school students who are very well-read in their field of computational biology. They demonstrate a college-level and above understanding of how machine learning models are built and tested for human diseases, particularly for neuroscience."
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