• Technology Introduction

We developed state-of-art artificial intelligence from retrospective data of acute leukemia patients to create two services:

1. Residual disease detection: an advanced algorithm to perform multicolor flow cytometry analysis on bone marrow specimens of acute leukemia patients.
2. Relapse and Mortality Prediction: a comprehensive risk stratification and outcome prediction models for acute myeloid leukemia patients using historical examination and treatment records.

 

• Scientific Innovation

1. The residual disease detection model could reduce the interpretation time from 20 minutes to 7 seconds for each sample with an accuracy of 90%
2. The outcome prediction model could reach over 80% accuracy in next-3-month relapse and survival prediction.

 

• This technology won the Futuretech Breakthrough Award in 2018 Future Tech Expo.

 

• Institutes

National Tsing Hua University and National Taiwan University Hospital
Yu-Fen Wang/ahead.taiwan@gmail.com