AIMC Topic: Deep Learning

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Deep Augmented Metric Learning Network for Prostate Cancer Classification in Ultrasound Images.

IEEE journal of biomedical and health informatics Mar 6, 2025
Prostate cancer screening often relies on cost-intensive MRIs and invasive needle biopsies. Transrectal ultrasound imaging, as a more affordable and non-invasive alternative, faces the challenge of high inter-class similarity and intra-class variabil...
Ultrasonography Male Prostatic Neoplasms Deep Learning Humans Prostate Image Interpretation, Computer-Assisted
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Multimodal Drug Target Binding Affinity Prediction Using Graph Local Substructure.

IEEE journal of biomedical and health informatics Mar 6, 2025
Predicting the binding affinity of drug target is essential to reduce drug development costs and cycles. Recently, several deep learning-based methods have been proposed to utilize the structural or sequential information of drugs and targets to pred...
Drug Discovery Deep Learning Humans Algorithms Proteins Pharmaceutical Preparations Protein Binding Computational Biology
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Property-Guided Few-Shot Learning for Molecular Property Prediction With Dual-View Encoder and Relation Graph Learning Network.

IEEE journal of biomedical and health informatics Mar 6, 2025
Molecular property prediction is an important task in drug discovery. However, experimental data for many drug molecules are limited, especially for novel molecular structures or rare diseases which affect the accuracy of many deep learning methods t...
Deep Learning Algorithms Drug Discovery Humans Machine Learning
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BINDTI: A Bi-Directional Intention Network for Drug-Target Interaction Identification Based on Attention Mechanisms.

IEEE journal of biomedical and health informatics Mar 6, 2025
The identification of drug-target interactions (DTIs) is an essential step in drug discovery. In vitro experimental methods are expensive, laborious, and time-consuming. Deep learning has witnessed promising progress in DTI prediction. However, how t...
Proteins Humans Deep Learning Neural Networks, Computer Computational Biology Drug Discovery
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AEGNN-M:A 3D Graph-Spatial Co-Representation Model for Molecular Property Prediction.

IEEE journal of biomedical and health informatics Mar 6, 2025
Improving the drug development process can expedite the introduction of more novel drugs that cater to the demands of precision medicine. Accurately predicting molecular properties remains a fundamental challenge in drug discovery and development. Cu...
Neural Networks, Computer Drug Discovery Humans Deep Learning Cell Line, Tumor
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Dual Representation Learning for Predicting Drug-Side Effect Frequency Using Protein Target Information.

IEEE journal of biomedical and health informatics Mar 6, 2025
Knowledge of unintended effects of drugs is critical in assessing the risk of treatment and in drug repurposing. Although numerous existing studies predict drug-side effect presence, only four of them predict the frequency of the side effects. Unfort...
Drug-Related Side Effects and Adverse Reactions Computational Biology Proteins Humans Deep Learning
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Prediction of Drug-Target Interactions With High- Quality Negative Samples and a Network-Based Deep Learning Framework.

IEEE journal of biomedical and health informatics Mar 6, 2025
Identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared to traditional experimental methods, computer-based methods for predicting DTIs can significantly reduce the time and financial burdens of drug develop...
Proteins Pharmaceutical Preparations Deep Learning Computational Biology Gene Ontology Humans Neural Networks, Computer Drug Discovery
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Semantic-Enhanced Graph Contrastive Learning With Adaptive Denoising for Drug Repositioning.

IEEE journal of biomedical and health informatics Mar 6, 2025
The traditional drug development process requires a significant investment in workforce and financial resources. Drug repositioning as an efficient alternative has attracted much attention during the last few years. Despite the wide application and s...
Machine Learning Algorithms Humans Drug Repositioning Databases, Factual Semantics Deep Learning
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Decoding Drug Response With Structurized Gridding Map-Based Cell Representation.

IEEE journal of biomedical and health informatics Mar 6, 2025
A thorough understanding of cell-line drug response mechanisms is crucial for drug development, repurposing, and resistance reversal. While targeted anticancer therapies have shown promise, not all cancers have well-established biomarkers to stratify...
Humans Computational Biology Neural Networks, Computer Deep Learning Neoplasms Cell Line, Tumor Antineoplastic Agents
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Enhancing Drug Repositioning Through Local Interactive Learning With Bilinear Attention Networks.

IEEE journal of biomedical and health informatics Mar 6, 2025
Drug repositioning has emerged as a promising strategy for identifying new therapeutic applications for existing drugs. In this study, we present DRGBCN, a novel computational method that integrates heterogeneous information through a deep bilinear a...
Humans Computational Biology Drug Repositioning Neural Networks, Computer Deep Learning
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