<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/82c917940ada471181dc58064c4f75d3&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/82c917940ada471181dc58064c4f75d3-00001.gif</thumbnail_url><duration>150.241</duration><title>Gemini AI Hackathon Project Demonstration</title><description>In this video, I will be demonstrating the project we developed for the Gemini AI hackathon. The project focuses on using machine learning to detect brain tumors from x-ray images and providing a comforting explanation of the detected tumor class. I will walk you through the basic concept of the project and showcase the web application interface. Please note that the generated report is not professional medical advice, and it is important to consult with a doctor for treatment options.</description></oembed>