Association rule mining has gained much popularity in facilitating disease diagnosis and the
healthcare industry's decision-making process. The cases of Drug Resistance Tuberculosis …

Chronic diseases have been among the major concerns in medical fields since they may
cause a heavy burden on healthcare resources and disturb the quality of life. In this paper …

Big IoT data is inherently distributed, high-dimensional, irregular, and sparse in nature. Fog
computing model in its original form is by no means the optimal solution for mining big IoT …

Sparseness is the distinctive aspect of big data generated by numerous applications at
present. Furthermore, several similar records exist in real-world sparse datasets. Based on …

Sparseness is often witnessed in big data emanating from a variety of sources, including IoT,
pervasive computing, and behavioral data. Frequent itemset mining is the first and foremost …

Modern algorithms for mining frequent itemsets face noteworthy deterioration of
performance when minimum support tends to decrease, especially for sparse datasets. Long …

A considerable fraction of the female workforce worldwide is making ends meet by doing
various jobs informally at home or in nearby places, rather than at employers' premises. The …

Chronic diseases may cause heavy burden on health care resources and disturb the quality
of life. Chronic Obstructive Pulmonary Disease (COPD) is an important chronic disease …

This research proposes machine learning techniques to develop models that would facilitate
decision-making in health informatics. It focuses on using efficient machine learning …

Medical data mining has great potential for exploring the hidden pattern in the data sets of
the medical domain. A predictive modeling approach of Data Mining has been …