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Artificial Intelligence-based Prediction of Acute Leukemia: a free and open-source software package built in R, with a user-friendly interface provided via Shiny, that enables clinical hematologists and biologists to diagnose the three main subtypes of acute leukemia based solely on 10 routine biological parameters.
A web app that uses a custom-built Keras model to recognize and classify white blood cells from microscopic images. It can distinguish between different types of WBCs and identify artifacts and bursted cells. I created this app as a way to explore image recognition technologies and to learn how to develop Keras models from scratch.
SCCRIP (Sickle Cell Clinical Research and Intervention Program) established a longitudinal cohort at multiple sites with Sickle Cell Disease (SCD) in 2014 managed by St. Jude Clinical Hematology. A new collaborator for SCCRIP has longitudinal data for 600 SCD patients in OMOP CDM format and this effort is to convert OMOP CDM to SCCRIP format.
This repository contains White Blood Cells (WBC) samples. This dataset is produced in Embedded System and Integrated Circuit Design Laboratory, Electrical Engineering Department, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand. The images are already labeled by our team from our collaborative researcher from Faculty of Medici…