The remarkable advancements in biotechnology and public healthcare infrastructures have
led to a momentous production of critical and sensitive healthcare data. By applying …

Convolutional neural networks (CNNs) have been extensively utilized in medical image
processing to automatically extract meaningful features and classify various medical …

Given a specific decision model for two decision problems faced by a decision maker,
decision parameters can be learned from the accumulated historical data. In general, more …

For over two decades, detecting rare events has been a challenging task among
researchers in the data mining and machine learning domain. Real-life problems inspire …

Proactive treatment of cancer, characterized by early detection and intervention is one of the
main focus of the next-generation healthcare systems for predictive, timely detection and …

The accumulated historical data are beneficial for generating solutions that are more
satisfactory to decision makers because their preferences and experience are characterized …

Predictive modeling is becoming an essential tool for clinical decision support, but health
systems with smaller sample sizes may construct suboptimal or overly specific models …

In healthcare, building a supervised learning system faces the challenge of access to a
large, labeled dataset. To overcome this problem, we propose a deep transfer learning …

Breast cancer is an important global health issue affecting women, leading to death. Early
detection is the best way to improve detection and survival rates. Deep learning (DL) and …

The rapid advancement of information technology (IT) and communication techniques in the
last decade has triggered the advent of the novel concept of the Internet of Things (IoT). It …