Author(s)

Jiahe Yan, Emily Tucci, Nathaniel Jaffe

Trinity-Pawling School, Pawling, NY, USA.

Karyotype analysis has significant clinical importance. Effectively detecting the exact abnormity of chromosomes will contribute to the diagnosis of certain diseases. In this paper, I presented a convenient and reliable system that was capable of detecting t(9;22) chromosome translocation, a specific chromosomal abnormity in CML patients. The functions of this system were based on deep learning algorithms, and I created a classification system using ResNet. The model could effectively detect t(9;22) translocation based on images of chromosomes 9 and 22. This model achieves a 97.5% accuracy on the validation set.

Karyotype, t(9;22) Chromosomal Translocation, ResNet, Deep Learning

Yan, J. , Tucci, E. and Jaffe, N. (2019) Detection of t(9;22) Chromosome Translocation Using Deep Residual Neural Network. Journal of Computer and Communications, 7, 102-111. doi: 10.4236/jcc.2019.712010.