SP-DTI: Subpocket-Informed Transformer for Drug–Target Interaction Prediction

Chemistry, Medicinal Chemistry, Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering,
Drug-Target Interaction   Deep Learning   Subpocket Analysis   Transformer Model   Drug Discovery  

Academic Background Drug-Target Interaction (DTI) prediction is a critical step in drug discovery, significantly reducing the cost and time of experimental screening. However, despite the advancements in deep learning that have improved the accuracy of DTI prediction, existing methods still face two major challenges: lack of generalizability and ne...

ABVS Breast Tumour Segmentation via Integrating CNN with Dilated Sampling Self-Attention and Feature Interaction Transformer

Information Science, Artificial Intelligence, Medicine, Medical Imaging,
Breast Tumour Segmentation   Automated Breast Volume Scanner   3D Transformer-CNN Segmentation Network   Mask Image Modelling   Deep Learning   Medical Image Analysis   Self-Supervised Learning  

ABVS Breast Tumor Segmentation Research Based on CNN and Dilated Sampling Self-Attention Academic Background Breast cancer is the second most common cancer worldwide, and early and accurate detection is crucial for improving patient prognosis and reducing mortality. Although various imaging techniques (such as X-ray mammography, magnetic resonance ...

Deep Reconstruction Framework with Self-Calibration Mechanisms for Accelerated Chemical Exchange Saturation Transfer Imaging

Information Science, Artificial Intelligence, Medicine, Medical Imaging, Life Sciences, Bioengineering,
Chemical Exchange Saturation Transfer Imaging   Deep Learning   Image Reconstruction   Self-Calibration   Fast Imaging  

Application of the Deep Reconstruction Framework with Self-Calibration Mechanisms (DEISM) in Accelerated Chemical Exchange Saturation Transfer Imaging Academic Background Chemical Exchange Saturation Transfer (CEST) imaging is a highly sensitive molecular magnetic resonance imaging technique capable of detecting biomolecules associated with various...

SigWavNet: Learning Multiresolution Signal Wavelet Network for Speech Emotion Recognition

Information Science, Computer Science, Artificial Intelligence,
Speech Emotion Recognition   Wavelet Transform   Deep Learning   Convolutional Neural Network   Bidirectional Gated Recurrent Unit  

Application of Multiresolution Signal Wavelet Network in Speech Emotion Recognition: SigWavNet Academic Background Speech Emotion Recognition (SER) plays a crucial role in human-computer interaction and psychological assessment. It identifies the speaker’s emotional state by analyzing speech signals, with wide applications in emergency call centers...

Leveraging Pharmacovigilance Data to Predict Population-Scale Toxicity Profiles of Checkpoint Inhibitor Immunotherapy

Information Science, Computer Science, Medicine, Oncology, Life Sciences, Immunology,
Pharmacovigilance   Checkpoint Inhibitors   Toxicity Prediction   Deep Learning   Cancer Immunotherapy   Population Analysis   Dynamic Graph Convolutional Network  

Predicting and Monitoring the Toxicity of Immune Checkpoint Inhibitors: Breakthrough Application of the DysPred Deep Learning Framework Academic Background Immune checkpoint inhibitors (ICIs) represent a major breakthrough in cancer immunotherapy in recent years, enhancing the body’s antitumor immune response by inhibiting immune checkpoint signali...

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...