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Project Descriptions

Alright, so let's talk about explainable AI! You know, AI models are doing some amazing things these days, but sometimes they can be like black boxes, making decisions without giving us a clear idea of how they arrived at those conclusions. That's where explainable AI steps in to save the day!

Explainable AI is all about making AI models more transparent and understandable. It helps us humans get insights into the inner workings of these complex models. And one cool technique we're diving into is Grad-CAM, short for Gradient-weighted Class Activation Mapping.

Now, here's the plan: I'm going to apply Grad-CAM to Chest X-Ray Images, specifically those related to Pneumonia. By using Grad-CAM, we'll be able to visualize and understand which areas of the X-ray image contribute the most to the model's decision-making process. It's like shining a spotlight on the important regions that help the AI model identify signs of pneumonia.

With this explainable AI technique in place, we can gain deeper insights into how the AI model is analyzing the X-ray images and what factors it's considering when making predictions. This can be incredibly useful for medical professionals, researchers, and even patients to better understand the AI's diagnostic process.