Cancer diagnosis using generative adversarial networks based on deep learning from imbalanced data

Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks

(2020) Mohamed Marouf et al.   Nature Communications

Wasserstein GAN-Based Small-Sample Augmentation for New-Generation Artificial Intelligence: A Case Study of Cancer-Staging Data in Biology

(2019) Yufei Liu et al.   Engineering

A comprehensive data level analysis for cancer diagnosis on imbalanced data

(2019) Sara Fotouhi et al.   JOURNAL OF BIOMEDICAL INFORMATICS

Generative Adversarial Networks: An Overview

(2018) Antonia Creswell et al.   IEEE SIGNAL PROCESSING MAGAZINE

Applications of Deep Learning in Biomedicine

(2016) Polina Mamoshina et al.   MOLECULAR PHARMACEUTICS

A new automatic mass detection method for breast cancer with false positive reduction

(2015) Xiaoming Liu et al.   NEUROCOMPUTING

Prediction of human breast and colon cancers from imbalanced data using nearest neighbor and support vector machines

(2014) Abdul Majid et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

A Classification Framework Applied to Cancer Gene Expression Profiles

(2013) Hussein Hijazi et al.   Journal of Healthcare Engineering

MWMOTE--Majority Weighted Minority Oversampling Technique for Imbalanced Data Set Learning

(2012) Sukarna Barua et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

DBSMOTE: Density-Based Synthetic Minority Over-sampling TEchnique

(2011) Chumphol Bunkhumpornpat et al.   APPLIED INTELLIGENCE

Differential expression analysis for sequence count data

(2010) Simon Anders et al.   GENOME BIOLOGY

CLASSIFICATION OF IMBALANCED DATA: A REVIEW

(2009) YANMIN SUN et al.   INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE