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 …

Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …

Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …

Due to the high availability of large-scale annotated image datasets, paramount progress
has been made in deep convolutional neural networks (CNNs) for image classification tasks …

Background Diabetics has become a serious public health burden in China. Multiple
complications appear with the progression of diabetics pose a serious threat to the quality of …

One of the leading forms of cancer is colorectal cancer (CRC), which is responsible for
increasing mortality in young people. The aim of this paper is to provide an experimental …

Early quantitative structure-activity relationship (QSAR) technologies have unsatisfactory
versatility and accuracy in fields such as drug discovery because they are based on …

This paper presents a review of deep learning (DL) in multi-organ segmentation. We
summarized the latest DL-based methods for medical image segmentation and applications …

Chest Radiograph or Chest X-ray (CXR) is a common, fast, non-invasive, relatively cheap
radiological examination method in medical sciences. CXRs can aid in diagnosing many …

Objectives Many deep learning-based predictive models evaluate the waveforms of
electrocardiograms (ECGs). Because deep learning-based models are data-driven, large …