Project History

The Peter Moss Acute Myeloid / Lymphoblastic Leukemia AI Research Project was created after Peter was diagnosed with Acute Myeloid Leukemia and given a few weeks to live. At the time there was little in depth information/datasets easily available online or through the doctors. A Facebook post by one of Peter's grandsons, Adam Milton-Barker, in Artificial Intelligence & Deep Learning (AIDL) Group on Facebook brought the project to the attention of Ho Leung Ng, Associate Professor of Biochemistry & Molecular Biophysics at Kansas State University. As a leukemia researcher, Ho was able to share information of datasets, research papers and access to people who are researching/volunteering their time/experience to early detection and drug discovery for Acute Myeloid and Lymphoblastic Leukemia.

During a visit to his family in the United States, Adam was able to speak to doctors at the Hematology Oncology Center in Port St Lucie, one of the centers that assisted Peter during his battle with AML. They explained a lot of things including how with AML, there is 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 as blood tests were all clear. It may be possible that something was missed, and AI may be the perfect tool to find that something.

The advice that the doctors gave in Port St Lucie was to try to work backwards from the point of diagnosis, trying to catch some sort of pattern, or anything that was missed during the previous test. AI is good at seeing patterns we as humans may miss, but the problem is getting hold of the right type of data needed for convolutional neural networks, or AI network of any kind. The obvious privacy restrictions means that it is not easy to obtain data, therefore the project relies on the help of others in the field who have dedicated their time to create open datasets.

TThe project is being coordinated by a group of volunteers with experience in computer vision / natural language processing, Leukemia research, Biochemistry, Molecular Biophysics, Immunology and Bioinformation.