Computational intelligence and neuroscience
Aug 28, 2022
The entire auditing process is complicated and tedious and requires a lot of human resources. Therefore, the intelligent development of auditing is the general trend. In order to improve the audit quality, this paper establishes an intelligent financ...
INTRODUCTION: The purpose of this study is to use deep learning and machine learning to learn and classify patients with cutaneous melanoma with different prognoses and to explore the application value of deep learning in the prognosis of cutaneous m...
Microsatellite instability (MSI) status is an important prognostic marker for various cancers. Furthermore, because immune checkpoint inhibitors are much more effective in tumors with high level of MSI (MSI-H), MSI status is routinely tested in multi...
OBJECTIVES: The prediction of primary treatment failure (PTF) is necessary for patients with diffuse large B-cell lymphoma (DLBCL) since it serves as a prominent means for improving front-line outcomes. Using interim F-fluoro-2-deoxyglucose ([F]FDG) ...
Ulcerative colitis (UC) belongs to the inflammatory bowel disease (IBD) family, which is mainly caused by inflammation of the tissue in the colon and rectum. The severity of this infection can radically affect the patient's overall well-being. Althou...
BACKGROUND: Time-resolved 4D cone beam-computed tomography (4D-CBCT) allows a daily assessment of patient anatomy and respiratory motion. However, 4D-CBCTs suffer from imaging artifacts that affect the CT number accuracy and prevent accurate proton d...
Chest X-ray (CXR) imaging is one of the most common diagnostic imaging techniques in clinical diagnosis and is usually used for radiological examinations to screen for thorax diseases. In this paper, we propose a novel computer-aided diagnosis (CAD) ...
Automatic segmentation of glioma and its subregions is of great significance for diagnosis, treatment and monitoring of disease. In this paper, an augmentation method, called TensorMixup, was proposed and applied to the three dimensional U-Net archit...
Pathogenic bacterial infections, exacerbated by increasing antimicrobial resistance, pose a major threat to human health worldwide. Extracellular vesicles (EVs), secreted by bacteria and acting as their "long-distance weapons", play an important role...
We have developed deep learning models for automatic identification of the maternal heart rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The models can be used to preprocess FHR data prior to automated analy...
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