Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …

Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

In this paper, we first describe the basics of the field of cancer diagnosis, which includes
steps of cancer diagnosis followed by the typical classification methods used by doctors …

Deep learning has rapidly advanced in various fields within the past few years and has
recently gained particular attention in the radiology community. This article provides an …

Compared with common deep learning methods (eg, convolutional neural networks),
transfer learning is characterized by simplicity, efficiency and its low training cost, breaking …

In this paper, we aim to provide a survey on the applications of deep learning for cancer
detection and diagnosis and hope to provide an overview of the progress in this field. In the …

The advent of deep learning has brought great change to the community of computer
science and also revitalized numerous fields where traditional machine learning methods …

As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data
processing techniques. One such technique, deep learning (DL), has become a remarkably …

As the most common examination tool in medical practice, chest radiography has important
clinical value in the diagnosis of disease. Thus, the automatic detection of chest disease …

Cervical cancer is one of the main reasons of death from cancer in women. The complication
of this cancer can be limited if it is diagnosed and treated at an early stage. In this paper, we …