AdamMiltonBarker / AML-Project-Research

A public repo of open Acute Myeloid Leukemia research papers discovered during project R&D

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AML AI Research Project

Peter Moss Acute Myeloid Leukemia AI Research Project

Documenting research/development and data for the Peter Moss AML (Acute Myeloid Leukemia) AI Research Project. The AML AI Research Project is open source and free to use (LICENSE) with the goals of researching and developing various Artificial Intelligence techniques to help detect AML and discover new drugs.

The AML AI Research Project is being organized and developed by a team of volunteers with experience in Leukemia research, computer vision, biochemistry & molecular biophysics among other areas of expertise. The team is currently made up of:

Team Member Position
Adam Milton-Barker Bigfinite IoT Network Engineer & Intel Software Innovator
Ho Leung Ng Kansas State University, Dept. Biochemistry & Molecular Biophysics
John LaRocco Former Humai Head of Engineering, LA, USA
Amita Kapoor Associate Professor @ Delhi University, New Dehli, India

Project structure

The following lays out the current project structure:

AML Project Research

A public repo of open Acute Myeloid Leukemia research papers discovered during project R&D. Related Repository

Project Description
Papers A database of open research papers on Acute Myeloid Leukemia
Datasets A database of open datasets on Acute Myeloid Leukemia

AML Classifiers

Research and development projects for detection/early detection of Acute Myeloid Leukemia. Related Repository

Project Description
Python Classifiers programmed in Python
Java Classifiers programmed in Java

AML Drug Discovery

Research and development projects for drug discovery for Acute Myeloid Leukemia. Related Repository

Project Description

AML Detection System

Acute Myeloid Leukemia Detection System with Intel technologies. Related Repository

Project Description
Android An Android application for managing and classifying data. Uses facial recognition for authentication.
Chatbot A REST API hosting an endpoint for Natural Language Understanding. Trained on knowledge of AML.
Classifier A REST API hosting an endpoint for classifying images using Convolutional Neural Networks.
Security A REST API hosting an endpoint for authentication using Siamese Neural Networks
Server A local server hosting a web based UI for managing and classifying data. Uses facial recognition for authentication.

Research papers

We will keep an up to date record of public research papers that we come across whilst developing the projects that make up the AML AI Research Project.

Papers Description Link
Research Papers Lists of research papers discovered during R&D List of papers
Convolutional Neural Networks for Acute Myeloid Leukemia Lists of research papers on Convolutional Neural Networks for Acute Myeloid Leukemia List of papers

Papers used in project

Papers used during project research and development.

Paper Description Link
Leukemia Blood Cell Image Classification Using Convolutional Neural Network T. T. P. Thanh, Caleb Vununu, Sukhrob Atoev, Suk-Hwan Lee, and Ki-Ryong Kwon Paper

Datasets

We will keep an up to date record of public datasets that we come across whilst developing the AML AI Research Project.

Dataset Description Link
Research Datasets Lists of datasets discovered during R&D List of datasets

Datasets used in project

Datasets used during project research and development.

Dataset Description Link
Acute Lymphoblastic Leukemia Image Database for Image Processing Created by Fabio Scotti, Associate Professor Dipartimento di Informatica, UniversitĂ  degli Studi di Milano. Dataset

Contributing

We welcome contributions of the project. Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests.

Versioning

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

License

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

Bugs/Issues

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