The proliferation of big data has brought an urgent demand for privacy-preserving data
publishing. Traditional solutions to this demand have limitations on effectively balancing the …

The random forest algorithm could be enhanced and produce better results with a well-
designed and organized feature selection phase. The dependency structure between the …

DNN testing is a critical way to guarantee the quality of DNNs. To obtain test oracle
information, DNN testing requires a huge cost to label test inputs, which greatly affects the …

Designing faithful yet accurate AI models is challenging, particularly in the field of individual
treatment effect estimation (ITE). ITE prediction models deployed in critical settings such as …

One of the key topics of research in the Health Care Management system (HMS) is the early
forecast of heart disease. Only by foreseeing cardiac illnesses in advance can we minimize …

Predicting a patient's future health state through the analysis of their clinical records is an
emerging area in the field of intelligent medicine. It has the potential to assist healthcare …

The primary aim of this article is to propose a novel orchestration framework based on
Revocable Dynamic Hash Table (RDHT) for dynamic and secure access of Electronic …

Predicting the severity of an illness is crucial in intensive care units (ICUs) if a patient's life is
to be saved. However, most methods do not consider the correlations between features in …

Effective disease prediction based on electronic health records (EHR) is an important topic
in health informatics. The current methods usually use common deep-learning models for …

Machine learning has proven to be one of the efficient solutions for analyzing complex data
to perform identification and classification. With a large number of learning tools and …