Cervical cytology image classification is of great significance to the cervical cancer
diagnosis and prognosis. Recently, convolutional neural network (CNN) and visual …

Liver disease is a potentially asymptomatic clinical entity that may progress to patient death.
This study proposes a multi-modal deep neural network for multi-class malignant liver …

Achieving microscopy with large space-bandwidth products plays a key role in diagnostic
imaging and is widely significant in the overall field of clinical practice. Among quantitative …

Background: Early diagnosis of brain diseases is very important. Brain disease classification
is a common and complex topic in biomedical engineering. Therefore, machine learning …

Liver cancer ranks as the sixth most prevalent cancer among all cancers globally. Computed
tomography (CT) scanning is a non-invasive analytic imaging sensory system that provides …

Abstract Generative Adversarial Networks (GANs) have shown promising prospects and
achieved significant results in medical image analysis tasks. This article provides a …

Liver diseases represent a significant challenge to global healthcare systems, necessitating
accurate and timely diagnosis for effective intervention. However, the intricate nature of liver …

The term “Liver disease” refers to a broad category of disorders affecting the liver. There are
a variety of common liver ailments, such as hepatitis, cirrhosis, and liver cancer. Accurate …

This article explores the application of deep learning techniques to improve the accuracy of
feature enhancements in noisy images. A multitasking convolutional neural network (CNN) …

Liver cancer is a significant global health concern, with its prevalence steadily rising over the
years. The accurate detection and classification of liver cancer are pivotal for timely …