AIMC Topic: Deep Learning

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A Dynamic Model for Early Prediction of Alzheimer's Disease by Leveraging Graph Convolutional Networks and Tensor Algebra.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2025
Alzheimer's disease (AD) is a neurocognitive disorder that deteriorates memory and impairs cognitive functions. Mild Cognitive Impairment (MCI) is generally considered as an intermediate phase between normal cognitive aging and more severe conditions...
Early Diagnosis Electronic Health Records Humans Female Male Neural Networks, Computer Disease Progression Aged Deep Learning Cognitive Dysfunction Computational Biology Alzheimer Disease
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Enhancing Privacy-Preserving Cancer Classification with Convolutional Neural Networks.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2025
Precision medicine significantly enhances patients prognosis, offering personalized treatments. Particularly for metastatic cancer, incorporating primary tumor location into the diagnostic process greatly improves survival rates. However, traditional...
Privacy Computer Security Neural Networks, Computer Genomics Machine Learning Precision Medicine Computational Biology Humans Algorithms Neoplasms Confidentiality Deep Learning
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Session Introduction: AI and Machine Learning in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2025
Artificial Intelligence (AI) technologies are increasingly capable of processing complex and multilayered datasets. Innovations in generative AI and deep learning have notably enhanced the extraction of insights from both unstructured texts, images, ...
Clinical Decision-Making Deep Learning User-Computer Interface Computational Biology Man-Machine Systems Humans Artificial Intelligence Machine Learning
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DeepTransformer: Node Classification Research of a Deep Graph Network on an Osteoporosis Graph based on GraphTransformer.

Current computer-aided drug design Jan 1, 2025
BACKGROUND: Osteoporosis (OP) is one of the most common diseases in the elderly population. It is mostly treated with medication, but drug research and development have the disadvantage of taking a long time and having a high cost.
Humans Osteoporosis Neural Networks, Computer Deep Learning Artificial Intelligence
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Acceleration of Simultaneous Multislice Magnetic Resonance Fingerprinting With Spatiotemporal Convolutional Neural Network.

NMR in biomedicine Jan 1, 2025
Magnetic Resonance Fingerprinting (MRF) can be accelerated with simultaneous multislice (SMS) imaging for joint T and T quantification. However, the high inter-slice and in-plane acceleration in SMS-MRF causes severe aliasing artifacts, limiting the ...
Neural Networks, Computer Deep Learning Algorithms Humans Brain Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Automated tooth segmentation in magnetic resonance scans using deep learning - A pilot study.

Dento maxillo facial radiology Jan 1, 2025
OBJECTIVES: The main objective was to develop and evaluate an artificial intelligence model for tooth segmentation in magnetic resonance (MR) scans.
Pilot Projects Imaging, Three-Dimensional Magnetic Resonance Imaging Tooth Adult Male Deep Learning Humans Female
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Machine Learning Techniques to Infer Protein Structure and Function from Sequences: A Comprehensive Review.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
The elucidation of protein structure and function plays a pivotal role in understanding biological processes and facilitating drug discovery. With the exponential growth of protein sequence data, machine learning techniques have emerged as powerful t...
Computational Biology Proteins Databases, Protein Machine Learning Deep Learning Structure-Activity Relationship Natural Language Processing Protein Conformation Humans Neural Networks, Computer
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Deep Learning Applied to Diffusion-weighted Imaging for Differentiating Malignant from Benign Breast Tumors without Lesion Segmentation.

Radiology. Artificial intelligence Jan 1, 2025
Purpose To evaluate and compare the performance of different artificial intelligence (AI) models in differentiating between benign and malignant breast tumors at diffusion-weighted imaging (DWI), including comparison with radiologist assessments. Mat...
Humans Retrospective Studies Female Diagnosis, Differential Breast Breast Neoplasms Diffusion Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Aged Middle Aged Adult Deep Learning
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Cancer-Associated Lymphoid Aggregates in Histology Images: Manual and Deep Learning-Based Quantification Approaches.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
Quantification of lymphoid aggregates including tertiary lymphoid structures (TLS) with germinal centers in histology images of cancer is a promising approach for developing prognostic and predictive tissue biomarkers. In this article, we provide rec...
Image Processing, Computer-Assisted Staining and Labeling Germinal Center Neoplasms Deep Learning Tertiary Lymphoid Structures Humans Algorithms
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Evaluating gradient-based explanation methods for neural network ECG analysis using heatmaps.

Journal of the American Medical Informatics Association : JAMIA Jan 1, 2025
OBJECTIVE: Evaluate popular explanation methods using heatmap visualizations to explain the predictions of deep neural networks for electrocardiogram (ECG) analysis and provide recommendations for selection of explanations methods.
Deep Learning Electrocardiography Signal Processing, Computer-Assisted Humans Neural Networks, Computer
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