AIMC Topic: Deep Learning

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A Multimodal Consistency-Based Self-Supervised Contrastive Learning Framework for Automated Sleep Staging in Patients With Disorders of Consciousness.

IEEE journal of biomedical and health informatics Feb 10, 2025
Sleep is a fundamental human activity, and automated sleep staging holds considerable investigational potential. Despite numerous deep learning methods proposed for sleep staging that exhibit notable performance, several challenges remain unresolved,...
Humans Female Adult Signal Processing, Computer-Assisted Supervised Machine Learning Electrooculography Sleep Stages Male Deep Learning Electroencephalography Consciousness Disorders
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Attention-Based Q-Space Deep Learning Generalized for Accelerated Diffusion Magnetic Resonance Imaging.

IEEE journal of biomedical and health informatics Feb 10, 2025
Diffusion magnetic resonance imaging (dMRI) is a non-invasive method for capturing the microanatomical information of tissues by measuring the diffusion weighted signals along multiple directions, which is widely used in the quantification of microst...
Deep Learning Brain Diffusion Magnetic Resonance Imaging Image Processing, Computer-Assisted Humans Adult Connectome Male Algorithms
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Interpretable Dynamic Directed Graph Convolutional Network for Multi-Relational Prediction of Missense Mutation and Drug Response.

IEEE journal of biomedical and health informatics Feb 10, 2025
Tumor heterogeneity presents a significant challenge in predicting drug responses, especially as missense mutations within the same gene can lead to varied outcomes such as drug resistance, enhanced sensitivity, or therapeutic ineffectiveness. These ...
Mutation, Missense Antineoplastic Agents Neural Networks, Computer Deep Learning Neoplasms Computational Biology Humans
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One-shot learning for generalization in medical image classification across modalities.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 9, 2025
Generalizability is one of the biggest challenges hindering the advancement of medical sensing technologies across multiple imaging modalities. This issue is further impaired when the imaging data is limited in scope or of poor quality. To tackle thi...
Tomography, X-Ray Computed Diagnostic Imaging Humans Machine Learning Deep Learning Algorithms Image Processing, Computer-Assisted
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Methods for estimating resting energy expenditure in intensive care patients: A comparative study of predictive equations with machine learning and deep learning approaches.

Computer methods and programs in biomedicine Feb 9, 2025
BACKGROUND: Accurate estimation of resting energy expenditure (REE) is critical for guiding nutritional therapy in critically ill patients. While indirect calorimetry (IC) is the gold standard for REE measurement, it is not routinely feasible in clin...
Male Calorimetry, Indirect Middle Aged Critical Care Humans Female Deep Learning Energy Metabolism Machine Learning Aged Rest Prospective Studies Adult Critical Illness Intensive Care Units
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Precision and efficiency in skin cancer segmentation through a dual encoder deep learning model.

Scientific reports Feb 9, 2025
Skin cancer is a prevalent health concern, and accurate segmentation of skin lesions is crucial for early diagnosis. Existing methods for skin lesion segmentation often face trade-offs between efficiency and feature extraction capabilities. This pape...
Skin Humans Neural Networks, Computer Skin Neoplasms Algorithms Deep Learning Image Processing, Computer-Assisted
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Flexible and cost-effective deep learning for accelerated multi-parametric relaxometry using phase-cycled bSSFP.

Scientific reports Feb 9, 2025
To accelerate the clinical adoption of quantitative magnetic resonance imaging (qMRI), frameworks are needed that not only allow for rapid acquisition, but also flexibility, cost efficiency, and high accuracy in parameter mapping. In this study, feed...
Brain Computer Simulation Deep Learning Cost-Benefit Analysis Signal-To-Noise Ratio Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans Neural Networks, Computer Monte Carlo Method
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An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.

Scientific reports Feb 9, 2025
Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strateg...
Receptors, Estrogen Receptors, Progesterone Biomarkers, Tumor Middle Aged Deep Learning Mammography Female Convolutional Neural Networks Receptor, ErbB-2 Adult ROC Curve Breast Neoplasms Humans Neural Networks, Computer
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Next-generation sequencing based deep learning model for prediction of HER2 status and response to HER2-targeted neoadjuvant chemotherapy.

Journal of cancer research and clinical oncology Feb 9, 2025
INTRODUCTION: For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 (HER2) is closely related to their prognosis and treatment decisions. This study aimed to further improve the accuracy and efficiency of HER2 amplific...
Mutation High-Throughput Nucleotide Sequencing Receptor, ErbB-2 Breast Neoplasms Biomarkers, Tumor Middle Aged Deep Learning Antineoplastic Combined Chemotherapy Protocols Neoadjuvant Therapy Prognosis Female Adult Humans
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Using deep feature distances for evaluating the perceptual quality of MR image reconstructions.

Magnetic resonance in medicine Feb 8, 2025
PURPOSE: Commonly used MR image quality (IQ) metrics have poor concordance with radiologist-perceived diagnostic IQ. Here, we develop and explore deep feature distances (DFDs)-distances computed in a lower-dimensional feature space encoded by a convo...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Algorithms Brain Deep Learning
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