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Peter Moss Acute Myeloid & Lymphoblastic Leukemia AI Research Project (@AMLResearchProject)

AMLResearchProject

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all-classifiers-2019

A collection of computer vision projects for Acute Lymphoblastic Leukemia classification/early detection.

Jupyter Notebook

all-detection-system-2019

Intel DevMesh AI Spotlight Award winner. Acute Lymphoblastic Leukemia Detection System 2019 uses Tensorflow 1.4.1 & Neural Compute Stick 1 to provide an intelligent network and diagnosis system. Project by Adam Milton-Barker.

all-arduino-nano-33-ble-sense-classifier

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.

AML-ALL-Research-Archive

A repository dedicated to sharing the AML/ALL related public information, papers, code and datasets that we come across through R&D.

all-jetson-nano-classifier

An Acute Lymphoblastic Leukemia classifier developed for the NVIDIA Jetson Nano. Jetson AI Certification project by Adam Milton-Barker.

Jupyter Notebook

all-oneapi-classifier-2020

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-Detection-System-For-Oculus-Rift

Acute Lymphoblastic Leukemia Detection System 2020 uses Tensorflow 2 & Oculus Rift to provide a virtual detection system. Project by Adam Milton-Barker.

Jupyter Notebook

ALL-Tensorflow-Classifier-2020

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.

Jupyter Notebook

all-fastai-2019

A series of Acute Lymphoblastic Leukemia CNNs programmed in Python using FastAI. Project by team member Salvatore Raieli.

Jupyter Notebook

aml-classifier-2021

Inspired by Human-level recognition of blast cells in acute myeloid leukemia with convolutional neural networks by Matek, C., Schwarz, S, Spiekermann, K., Marr, C. CapsNets. Project by Adam Milton-Barker

ALL-PyTorch-Segmentation-2021

Acute Lymphoblastic Leukemia classification using segmentation and the Acute Lymphoblastic Leukemia Image Database for Image Processing dataset. Programmed in Python using PyTorch.

all-fastai-2020

A series of Acute Lymphoblastic Leukemia CNNs programmed in Python using FastAI. Project by team member Salvatore Raieli.

Jupyter Notebook

contributing-guide

The contributing guide provides instructions on how to contribute to the Peter Moss Acute Myeloid and Lymphoblastic Leukemia AI Research Project.

all-detection-system-for-magic-leap-1

Acute Lymphoblastic Leukemia Detection System 2020 uses Tensorflow 2 & Magic Leap to provide a mixed reality detection system. Project by Adam Milton-Barker.

AML-Genomics-2021

An Acute Myeloid Leukemia diagnostics project based on the research outlined in Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics by Stefanie WarnatHerresthal, Konstantinos Perrakis, Bernd Taschler, Torsten Haferlach, Sach Mukherjee & Joachim L. Schultze.