DEV Community

Cover image for AI Models Achieve 99.8% Accuracy in Detecting Leukemia from Blood Cell Images
Mike Young
Mike Young

Posted on • Originally published at aimodels.fyi

AI Models Achieve 99.8% Accuracy in Detecting Leukemia from Blood Cell Images

This is a Plain English Papers summary of a research paper called AI Models Achieve 99.8% Accuracy in Detecting Leukemia from Blood Cell Images. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Overview

  • Research focuses on detecting Acute Lymphoblastic Leukemia (ALL) using deep learning
  • Compares performance of YOLOv11, YOLOv8, ResNet50, and Inception-ResNet-v2 models
  • Uses microscopic blood cell images to classify healthy vs leukemia cells
  • Achieves high accuracy rates across multiple models
  • Demonstrates potential for automated early cancer detection

Plain English Explanation

Cancer detection often relies on experts manually examining blood samples under microscopes. This research tests new computer systems that can automatically spot signs of [leukemia in blood samples](https://aimodels.fyi/papers/arxiv/acute-lymphoblastic-leukemia-diagnosis-employ...

Click here to read the full summary of this paper

API Trace View

Struggling with slow API calls? 👀

Dan Mindru walks through how he used Sentry's new Trace View feature to shave off 22.3 seconds from an API call.

Get a practical walkthrough of how to identify bottlenecks, split tasks into multiple parallel tasks, identify slow AI model calls, and more.

Read more →

Top comments (0)

A Workflow Copilot. Tailored to You.

Pieces.app image

Our desktop app, with its intelligent copilot, streamlines coding by generating snippets, extracting code from screenshots, and accelerating problem-solving.

Read the docs