The last decade has witnessed a steady embrace of genomic and personalized medicine by
senior government officials, industry leadership, health care providers, and the public …

Due to the huge amount of biological and medical data available today, along with well-
established machine learning algorithms, the design of largely automated drug development …

There is a pressing need for high-quality, effective means of designing, developing,
presenting, implementing, evaluating, and maintaining all types of clinical decision support …

We describe studies in molecular profiling and biological pathway analysis that use sparse
latent factor and regression models for microarray gene expression data. We discuss breast …

The advent of microarray technology has enabled scientists to simultaneously investigate
the expression of thousands of genes. Gene-expression profiling studies have provided a …

In the era of accelerating growth of genomic data, feature-selection techniques are believed
to become a game changer that can help substantially reduce the complexity of the data …

Bayesian methods are valuable, inter alia, whenever there is a need to extract information
from data that are uncertain or subject to any kind of error or noise (including measurement …

Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …

The discovery of drugs and its pipelines formulation is tough, long, and depend on various
factors. Machine Learning comes as a savior to this field and supplies different tools and …

To support large-scale biomedical research projects, organizations need to share person-
specific genomic sequences without violating the privacy of their data subjects. In the past …