Peter Moss Acute Myeloid & Lymphoblastic Leukaemia AI Research Project
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The Peter Moss Acute Myeloid & Lymphoblastic AI Research Project is an Asociación de Investigacion en Inteligencia Artificial Para la Leucemia Peter Moss research project focusing on the use of Artificial Intelligence in the battle against Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL).
The research project was founded in 2018 when Peter Moss was diagnosed with AML and given a few weeks to live. The research project was founded by Peter's eldest grandson, Adam Milton-Barker later joined by co-founders Prof. Ho Leung Ng and Dr Amita Kapoor. This research project was the foundations for what became Asociación de Investigacion en Inteligencia Artificial Para la Leucemia Peter Moss.
AML has no known warning signs, so early detection is very hard if not impossible. In Peter's case, the disease was completely missed in a standard blood test 1 month before being diagnosed terminal with AML. Adam was convinced that there must have been signs in that blood test, and possibly in earlier results, he set out to form a team of volunteers with the goals of using Artificial Intelligence for the early detection of Acute Myeloid Leukemia.
In loving memory of Peter Edward Moss, 5th Aug 1939 - 24th Aug 2019, who bravely battled Acute Myeloid Leukemia. A loving husband, father, grandfather and great grandfather.
We are honored to have been nominated in the category of Best Innovative Initiative in the Barcelona Health Hub Awards 2021.
The #BHHAwards recognizes actors in the health sector working to accelerate the adoption of innovation in the healthcare industry — so that the most relevant breakthroughs and disruptive technologies actually reach and make an impact in people’s life.
Please support our Association by voting for us in category 4 on the BHH Awards page.
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Repositories
- all-agx-xavier-classifier Public
An Acute Lymphoblastic Leukemia classifier developed for the NVIDIA AGX Xavier using Intel® oneAPI AI Analytics Toolkit, Intel® Optimization for Tensorflow*, and TensorRT.
- .github Public
- all-jetson-nano-classifier Public
An Acute Lymphoblastic Leukemia classifier developed for the NVIDIA Jetson Nano. Jetson AI Certification project by Adam Milton-Barker.
- all-arduino-nano-33-ble-sense-classifier Public
The ALL Arduino Nano 33 BLE Sense Classifier is an experiment to explore how low powered microcontrollers, specifically the Arduino Nano 33 BLE Sense, can be used to detect Acute Lymphoblastic Leukemia.
- contributing-guide Public
The contributing guide provides instructions on how to contribute to the Peter Moss Acute Myeloid and Lymphoblastic Leukemia AI Research Project.
- all-fastai-2019 Public
A series of Acute Lymphoblastic Leukemia CNNs programmed in Python using FastAI. Project by team member Salvatore Raieli.
- all-fastai-2020 Public
A series of Acute Lymphoblastic Leukemia CNNs programmed in Python using FastAI. Project by team member Salvatore Raieli.
- all-detection-system-for-magic-leap-1 Public
Acute Lymphoblastic Leukemia Detection System 2020 uses Tensorflow 2 & Magic Leap to provide a mixed reality detection system. Project by Adam Milton-Barker.
- all-oneapi-classifier-2020 Public
An Acute Lymphoblastic Leukemia classifier trained using Intel Distribution for Python and Intel Optimized Tensorflow (Tensorflow 2.1), and using OpenVINO to deploy the model on UP2 & Raspberry Pi.
- ALL-Tensorflow-Classifier-2020 Public
An Acute Lymphoblastic Leukemia CNN based on the proposed architecture in the Acute Leukemia Classification Using Convolution Neural Network In Clinical Decision Support System paper, using the Acute Lymphoblastic Leukemia Image Database for Image Processing dataset. Project by Adam Milton-Barker.
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