• Introduction
• DISCLAIMER
• Intel® DevMesh AI Spotlight Award
• Projects
• Intel® Technologies
• Related Events
• Related Team Publications
• Contributing
  • Contributors
• Versioning
• License
• Bugs/Issues

The Peter Moss Acute Myeloid & Lymphoblastic Leukemia Detection System is an opensource classifier with a locally hosted, database driven UI for data management, training, and running inference on Convolutional Neural Networks on the edge. This project was our official demo for 2019 and leverages Intel® technologies such as the UP2/UP2 AI Vision Dev Kit and Movidius NCS.

This project is made up of a number of components which work together to provide a locally hosted management system. Follow the completed tutorials below in the provided order. A full system setup requires Server, Facial-Auth, Data Augmentation, NCS1 Tensorflow Classifier, and Chatbot.

This project should be used for research purposes only. The purpose of the project is to show the potential of Artificial Intelligence for medical support systems such as diagnosis systems.

Although the classifier is accurate and shows good results both on paper and in real world testing, it is not meant to be an alternative to professional medical diagnosis.

Developers that have contributed to this repository have experience in using Artificial Intelligence for detecting certain types of cancer. They are not a doctors, medical or cancer experts.

Please use these systems responsibly.

In 2019 the Acute Lymphoblastic Leukemia Detection System 2019 was awarded the Intel® Devmesh AI Spotlight Award. Our project was one of 4 projects, and 1st from Europe, awarded the then new designation granted by Intel recognizing inspiring and breakthrough Artificial Intelligence projects in development from the Intel software community.

UP Squared & Movidius NCS1.

This project uses various Intel® technologies such as UP2, Intel® Movidius Neural Compute Stick 1 and Intel® AI DevCloud to enhance the training process and combine powerful CNNs with edge technologies for Internet of Things networks.

A number of our team members are Intel® Software Innovators, part of an Intel® program that supports independent developers with the latest Intel® hardware/software, speakerships & event opportunities, as well as technical advice and support through the various on and offline communities.

• Applied Analytics for clinical decision support (Bachelor Thesis) - Estela Cabezas

• Acute Myeloid/Lymphoblastic Leukemia Data Augmentation (Intel® AI Developer Program) - Adam Milton-Barker

• Inception V3 Deep Convolutional Architecture For Classifying Acute Myeloid/Lymphoblastic Leukemia (Intel® AI Developer Program) - Adam Milton-Barker

The Peter Moss Acute Myeloid & Lymphoblastic Leukemia AI Research project encourages and welcomes code contributions, bug fixes and enhancements from the Github.

Please read the CONTRIBUTING document for a full guide to forking our repositories and submitting your pull requests. You will also find information about our code of conduct on this page.

• Adam Milton-Barker - Asociacion De Investigation En Inteligencia Artificial Para La Leucemia Peter Moss President & Lead Developer, Sabadell, Spain

We use SemVer for versioning. For the versions available, see Releases.

This project is licensed under the MIT License - see the LICENSE file for details.

We use the repo issues to track bugs and general requests related to using this project.