Deep Learning Algorithms for Breast Cancer Detection in a UK Screening Cohort: As Stand-Alone Readers and Combined with Human Readers

Information Science, Artificial Intelligence, Medicine, Medical Imaging, Oncology,
Deep Learning   Breast Cancer Screening   Stand-Alone Reading   Human Reading   UK Cohort  

Deep Learning Algorithms in Breast Cancer Screening Academic Background Breast cancer is one of the most common cancers among women worldwide, and early screening is crucial for improving cure rates. Traditional Computer-Aided Detection (CAD) systems have been widely used in mammographic screening, particularly in the United States. However, while ...

Transformer for Object Re-Identification: A Survey

Information Science, Electronic Information, Computer Science, Automation, Artificial Intelligence,
Object Re-Identification   Transformer   Deep Learning   Cross-Modal Recognition   Video Analysis  

Background and Significance Object re-identification (Re-ID) is an essential task in computer vision aimed at identifying specific objects across different times and scenes. Driven by deep learning, particularly convolutional neural networks (CNNs), this field has made significant strides. However, the emergence of vision transformers has opened ne...

Revealing the Mechanisms of Semantic Satiation with Deep Learning Models

Revealing the Mechanisms of Semantic Satiation with Deep Learning Models

Information Science, Computer Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Biophysics,
Deep Learning   Semantic Satiation   Neural Network   Cognitive Mechanisms   Visual Cortex  

Deep Learning Model Reveals Mechanisms of Semantic Satiation Semantic satiation, the phenomenon where a word or phrase loses its meaning after being repeated many times, is a well-known psychological phenomenon. However, the micro-neural computational principles underlying this mechanism remain unknown. This paper uses a continuous coupled neural n...

EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records

EHR-HGCN: An Enhanced Hybrid Approach for Text Classification Using Heterogeneous Graph Convolutional Networks in Electronic Health Records

Information Science, Computer Science, Artificial Intelligence,
Electronic Health Records   Heterogeneous Graph Convolutional Networks   Text Classification   Natural Language Processing   Deep Learning  

EHR-HGCN: A Novel Hybrid Heterogeneous Graph Convolutional Network Method for Electronic Health Record Text Classification Academic Background With the rapid development of Natural Language Processing (NLP), text classification has become an important research direction in this field. Text classification not only helps us understand the knowledge b...

A Siamese-Transport Domain Adaptation Framework for 3D MRI Classification of Gliomas and Alzheimer’s Diseases

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Neurology, Medical Imaging, Oncology,
3D MRI   Gliomas   Alzheimer's Disease   Domain Adaptation   Deep Learning  

Classification of 3D MRI Gliomas and Alzheimer’s Disease Based on the Siamese-Transport Domain Adaptation Framework Background In computer-aided diagnosis, 3D magnetic resonance imaging (MRI) screening plays a vital role in the early diagnosis of various brain diseases, effectively preventing the deterioration of the condition. Glioma is a common m...