This study aims to systematically review prior research on the evaluation and benchmarking
of automated acute leukaemia classification tasks. The review depends on three reliable …

Context Acute leukaemia diagnosis is a field requiring automated solutions, tools and
methods and the ability to facilitate early detection and even prediction. Many studies have …

This paper aims to assist the administration departments of medical organisations in making
the right decision on selecting a suitable multiclass classification model for acute leukaemia …

Microarrays are still one of the major techniques employed to study cancer biology.
However, the identification of expression patterns from microarray datasets is still a …

DNA microarray datasets are characterized by a large number of features with very few
samples, which is a typical cause of overfitting and poor generalization in the classification …

This paper proposes a novel system of Leukemia detection based on Back-Propagation
Neural Network (BPNN) classifier optimized by Principal Component Analysis (PCA) and …

In this study, a new methodology is proposed to automatically determine six parameters of
artificial neural network using population‐based metaheuristics. We considered following …

The analysis of microarrays has the potential to identify and predict diseases predisposition,
such as cancer, opening a new path to better diagnosis and improved treatments …

摘要为了提高海量高维小样本数据的聚类准确率和效率, 提出一种基于递归文化基因和云计算
分布式计算的高维大数据聚类系统. 基于spark 分布式计算平台设计迭代的聚类系统 …

Stabilizing the complexity of Feedforward Neural Networks (FNNs) for the given
approximation task can be managed by defining an appropriate model magnitude which is …