We have had to wait over 30 years since the naive Bayes model was first introduced in 1960
for the so-called Bayesian network classifiers to resurge. Based on Bayesian networks …

Use of computer based decision tools to aid clinical decision making, has been a primary
goal of research in biomedical informatics. Research in the last five decades has led to the …

Multi-dimensional classification aims at finding a function that assigns a vector of class
values to a given vector of features. In this paper, this problem is tackled by a general family …

Abstract Models for predicting the probability of experiencing various health outcomes or
adverse events over a certain time frame (eg, having a heart attack in the next 5 years) …

Industrial Applications of Machine Learning shows how machine learning can be applied to
address real-world problems in the fourth industrial revolution, and provides the required …

Objective To determine whether a factorized version of the complement naïve Bayes (FCNB)
classifier can reduce the time spent by experts reviewing journal articles for inclusion in …

Abstract Models for predicting the risk of cardiovascular (CV) events based on individual
patient characteristics are important tools for managing patient care. Most current and …

Growing imperviousness and urbanization have increased peak flow magnitude which
results in flood events specifically during extreme conditions. Precise and reliable multi-step …

Parkinson's disease (PD) has broadly been associated with mild cognitive impairment
(PDMCI) and dementia (PDD). Researchers have studied surrogate, neuroanatomic …

Multi-dimensional classification is a cutting-edge problem, in which the values of multiple
class variables have to be simultaneously assigned to a given example. It is an extension of …