In the last few years, the application of Machine Learning approaches like Deep Neural
Network (DNN) models have become more attractive in the healthcare system given the …

Neural networks are powerful tools used widely for building cancer prediction models from
microarray data. We review the most recently proposed models to highlight the roles of …

Cancer is one of the most common causes of death worldwide and is, therefore, a prominent
area of biomedical research. Cancer is a genetic disease in which improperly functioning …

Breast cancer is the most frequent cancer in women and the second most frequent overall
after lung cancer. Although the 5-year survival rate of breast cancer is relatively high …

This paper introduces a novel algorithm for big data time series forecasting. Its main novelty
lies in its ability to deal with multivariate data, ie to consider multiple time series …

A new approach for big data forecasting based on the k-weighted nearest neighbours
algorithm is introduced in this work. Such an algorithm has been developed for distributed …

Electronic Health Records (EHRs) form major part of Medical Big Data (MBD) and are
enormous resources of knowledge. Mining EHRs can lead us to new generations of …

Breast cancer is a deadly disease which is most commonly diagnosed in women. It spreads
worldwide as the number of cases is increasing each day. The significant increase in cancer …

Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers
exciting developments at the intersection of computer science and statistics. While much of …

In this research, an extended random forest algorithm for multivariate time series several
steps forecasting is proposed. Peoposed method consists input layer and hidden layers …