Recent years have witnessed tremendous growth in the application of machine learning
(ML) and deep learning (DL) techniques in medical physics. Embracing the current big data …

The interest in machine learning (ML) has grown tremendously in recent years, partly due to
the performance leap that occurred with new techniques of deep learning, convolutional …

With the era of big data, the utilization of machine learning algorithms in radiation oncology
is rapidly growing with applications including: treatment response modeling, treatment …

With the development in technology, many other technologies like machine learning (ML),
deep learning, blockchain technology, Internet of Things, and quantum computing have …

Abstract Machine learning is an evolving branch of computational algorithms that are
designed to emulate human intelligence by learning from the surrounding environment …

Treatment planning plays an important role in the process of radiotherapy (RT). The quality
of the treatment plan directly and significantly affects patient treatment outcomes. In the past …

Background and purpose The use of artificial intelligence (AI)/machine learning (ML)
applications in radiation oncology is emerging, however no clear guidelines on …

The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …

Introduction: Deep Learning (DL) is a machine learning technique that uses deep neural
networks to create a model. The application areas of deep learning in radiation oncology …

Radiation oncology has always been deeply rooted in modeling, from the early days of
isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the …