Acute Myeloid Leukemia Classifier 2021

Acute Myeloid Leukemia Classifier 2021

Acute Myeloid Leukemia Classifier 2021 on Linkedin
The Acute Myeloid Leukemia (AML) Classifier is an implementation of a Convolutional Neural Network designed to assist with the early detection of Acute Myeloid Leukemia. The project is the focus of Juan Carlos Carrasco-Giménez' MSc Thesis: Acute Myeloid Leukemia classification using HIAS, and is 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 will be also considered as part of Juan-Carlos' master thesis in AI under the direction of Professor J.M. Jerez-Aragonés (School of Computer Science and Engineering, University of Málaga).

 

 

Introduction

The Acute Myeloid Leukemia (AML) Classifier is an implementation of a Convolutional Neural Network designed to assist with the early detection of Acute Myeloid Leukemia. The project is the focus of Juan Carlos Carrasco-Giménez' MSc Thesis: Acute Myeloid Leukemia classification using HIAS, and is 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 will be also considered as part of Juan-Carlos' master thesis in AI under the direction of Professor J.M. Jerez-Aragonés (School of Computer Science and Engineering, University of Málaga).



 

Project Contributors

Juan Carlos Carrasco-Giménez

Juan Carlos Carrasco-Giménez

Student Program Lead




Project Videos

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