With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …

Clinical oncology is experiencing rapid growth in data that are collected to enhance cancer
care. With recent advances in the field of artificial intelligence (AI), there is now a …

Interpretability in machine learning (ML) is crucial for high stakes decisions and
troubleshooting. In this work, we provide fundamental principles for interpretable ML, and …

In recent years, the development of artificial intelligence (AI) and the gradual beginning of
AI's research in the medical field have allowed people to see the excellent prospects of the …

Artificial intelligence (AI) is concretely reshaping the landscape and horizons of oncology,
opening new important opportunities for improving the management of cancer patients …

In considering the need of people all over the world for high-quality food, there has been a
recent increase in interest in the role of nondestructive and rapid detection technologies in …

Deep learning requires a large amount of data to perform well. However, the field of medical
image analysis suffers from a lack of sufficient data for training deep learning models …

Due to its automatic feature learning ability and high performance, deep learning has
gradually become the mainstream of artificial intelligence in recent years, playing a role in …

In the rapidly evolving landscape of organizational technologies, the integration of Artificial
Intelligence (AI) into Administrative Information Systems (AIS) stands out as a pivotal and …

Artificial Intelligence (AI) technologies have recently been applied to medical imaging for
diagnostic support. With respect to fetal ultrasound screening of congenital heart disease …