AIMC Topic: Deep Learning
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Towards prehospital risk stratification using deep learning for ECG interpretation in suspected acute coronary syndrome.
BMJ health & care informatics
Jun 6, 2025
OBJECTIVES: Most patients presenting with chest pain in the emergency medical services (EMS) setting are suspected of non-ST-elevation acute coronary syndrome (NSTE-ACS). Distinguishing true NSTE-ACS from non-cardiac chest pain based solely on the EC...
Personalized deep neural networks reveal mechanisms of math learning disabilities in children.
Science advances
Jun 6, 2025
Learning disabilities affect a substantial proportion of children worldwide, with far-reaching consequences for their academic, professional, and personal lives. Here we develop digital twins-biologically plausible personalized deep neural networks (...
Deep learning-based applicator selection between Syed and T&O in high-dose-rate brachytherapy for locally advanced cervical cancer: a retrospective study.
Physics in medicine and biology
Jun 6, 2025
High-dose-rate (HDR) brachytherapy is integral to the standard-of-care for locally advanced cervical cancer (LACC). Currently, selection of brachytherapy applicators relies on physician's clinical experience, which can lead to variability in treatmen...
The application of deep learning in economic analysis and marketing strategy formulation in the tourism industry.
PloS one
Jun 6, 2025
The tourism industry is ever-evolving in nature, as it operates in a global marketplace that has become progressively global and offers great potential due to technological advances. The tourism industry faces challenges in accurately forecasting eco...
Unsupervised deep clustering of high-resolution satellite imagery reveals phenotypes of urban development in Sub-Saharan Africa.
The Science of the total environment
Jun 5, 2025
Sub-Saharan Africa and other developing regions have urbanized extensively, leading to complex urban features with varying presence and types of roads, buildings and vegetation. We use a novel hierarchical deep learning framework and high-resolution ...
Comparative analysis of semantic-segmentation models for screen film mammograms.
Computers in biology and medicine
Jun 5, 2025
Accurate segmentation of mammographic mass is very important as shape characteristics of these masses play a significant role for radiologist to diagnose benign and malignant cases. Recently, various deep learning segmentation algorithms have become ...
Improving Covalent and Noncovalent Molecule Generation via Reinforcement Learning with Functional Fragments.
Journal of chemical information and modeling
Jun 5, 2025
Small-molecule drugs play a critical role in cancer therapy by selectively targeting key signaling pathways that drive tumor growth. While deep learning models have advanced drug discovery, there remains a lack of generative frameworks for covalent ...
Chemical Properties-Based Deep Learning Models for Recommending Rational Daily Diet Combinations to Diabetics Through Large-Scale Virtual Screening of α-Glucosidase Dietary-Derived Inhibitors and Verified In Vitro.
Journal of agricultural and food chemistry
Jun 5, 2025
The lack of suitable chemical research methodologies has hindered the discovery of rational daily diet combinations from large-scale dietary-derived compounds. Three deep learning models based on chemical properties for α-glucosidase inhibitors (AGIs...
Artificial intelligence-based detection of dens invaginatus in panoramic radiographs.
BMC oral health
Jun 5, 2025
OBJECTIVE: The aim of this study was to automatically detect teeth with dens invaginatus (DI) in panoramic radiographs using deep learning algorithms and to compare the success of the algorithms.
Construction of a deep learning-based predictive model to evaluate the influence of mechanical stretching stimuli on MMP-2 gene expression levels in fibroblasts.
Biomedical engineering online
Jun 5, 2025
BACKGROUND: Matrix metalloproteinase-2 (MMP-2) secretion homeostasis, governed by the multifaceted interplay of skin stretching, is a pivotal determinant influencing wound healing dynamics. This investigation endeavors to devise an artificial intelli...
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