Predicting the response, or sensitivity, of a clinical drug to a specific cancer type is an important research problem. By predicting the clinical drug response correctly, clinicians are able to understand patient-to-patient differences in drug sensi...
Journal of cancer research and clinical oncology
Jan 3, 2019
PURPOSE: Oral cancer is a complex wide spread cancer, which has high severity. Using advanced technology and deep learning algorithm early detection and classification are made possible. Medical imaging technique, computer-aided diagnosis and detecti...
Face recognition using a single reference image per subject is challenging, above all when referring to a large gallery of subjects. Furthermore, the problem hardness seriously increases when the images are acquired in unconstrained conditions. In th...
BACKGROUND: A direct blow to the knee is one way to injure the anterior cruciate ligament (ACL), e.g., during a football or traffic accident. Robot-assisted therapy (RAT) rehabilitation, simulating regular walking, improves walking and balance abilit...
BACKGROUND: Lung segmentation constitutes a critical procedure for any clinical-decision supporting system aimed to improve the early diagnosis and treatment of lung diseases. Abnormal lungs mainly include lung parenchyma with commonalities on CT ima...
AJR. American journal of roentgenology
Jan 2, 2019
OBJECTIVE: The purpose of this study is to evaluate the potential value of machine learning (ML)-based high-dimensional quantitative CT texture analysis in predicting the mutation status of the gene encoding the protein polybromo-1 (PBRM1) in patient...
Nowadays, automatic tumor detection from brain images is extremely significant for many diagnostic as well as therapeutic purposes, due to the unpredictable shape and appearance of tumors. In medical image analysis, the automatic segmentation of tumo...
IEEE journal of biomedical and health informatics
Jan 1, 2019
Automated tissue classification is an essential step for quantitative analysis and treatment of emphysema. Although many studies have been conducted in this area, there still remain two major challenges. First, different emphysematous tissue appears ...
IEEE transactions on neural networks and learning systems
Jan 1, 2019
This paper investigates the problem of extended dissipativity for Markovian jump neural networks (MJNNs) with a time-varying delay. The objective is to derive less conservative extended dissipativity criteria for delayed MJNNs. Toward this aim, an ap...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.