AIMC Topic: Deep Learning
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Deep learning-based Monte Carlo dose prediction for heavy-ion online adaptive radiotherapy and fast quality assurance: A feasibility study.
Medical physics
Jan 27, 2025
BACKGROUND: Online adaptive radiotherapy (OART) and rapid quality assurance (QA) are essential for effective heavy ion therapy (HIT). However, there is a shortage of deep learning (DL) models and workflows for predicting Monte Carlo (MC) doses in suc...
A deep-learning system integrating electrocardiograms and laboratory indicators for diagnosing acute aortic dissection and acute myocardial infarction.
International journal of cardiology
Jan 27, 2025
BACKGROUND: Acute Stanford Type A aortic dissection (AAD-type A) and acute myocardial infarction (AMI) present with similar symptoms but require distinct treatments. Efficient differentiation is critical due to limited access to radiological equipmen...
Automatic segmentation and volumetric analysis of intracranial hemorrhages in brain CT images.
European journal of radiology
Jan 27, 2025
BACKGROUND: Intracranial hemorrhages (ICH) are life-threatening conditions that require rapid detection and precise subtype classification. Automated segmentation and volumetric analysis using deep learning can enhance clinical decision-making.
Detecting IDH and TERTp mutations in diffuse gliomas using H-MRS with attention deep-shallow networks.
Computers in biology and medicine
Jan 27, 2025
BACKGROUND: Preoperative and noninvasive detection of isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) mutations in glioma is critical for prognosis and treatment planning. This study aims to develop deep lear...
A deep learning pipeline for three-dimensional brain-wide mapping of local neuronal ensembles in teravoxel light-sheet microscopy.
Nature methods
Jan 27, 2025
Teravoxel-scale, cellular-resolution images of cleared rodent brains acquired with light-sheet fluorescence microscopy have transformed the way we study the brain. Realizing the potential of this technology requires computational pipelines that gener...
LiteMamba-Bound: A lightweight Mamba-based model with boundary-aware and normalized active contour loss for skin lesion segmentation.
Methods (San Diego, Calif.)
Jan 27, 2025
In the field of medical science, skin segmentation has gained significant importance, particularly in dermatology and skin cancer research. This domain demands high precision in distinguishing critical regions (such as lesions or moles) from healthy ...
Beyond averaging: A transformer approach to decoding event related brain potentials.
NeuroImage
Jan 27, 2025
The objective of this study is to assess the potential of a transformer-based deep learning approach applied to event-related brain potentials (ERPs) derived from electroencephalographic (EEG) data. Traditional methods involve averaging the EEG signa...
Deep Learning-Assisted Fluorescence Single-Particle Detection of Fumonisin B Powered by Entropy-Driven Catalysis and Argonaute.
Analytical chemistry
Jan 27, 2025
Timely and accurate detection of trace mycotoxins in agricultural products and food is significant for ensuring food safety and public health. Herein, a deep learning-assisted and entropy-driven catalysis (EDC)-Argonaute powered fluorescence single-p...
QuanFormer: A Transformer-Based Precise Peak Detection and Quantification Tool in LC-MS-Based Metabolomics.
Analytical chemistry
Jan 27, 2025
In metabolomic analysis based on liquid chromatography coupled with mass spectrometry, detecting and quantifying intricate objects is a massive job. Current peak picking methods still cause high rates of incorrectly picked peaks to influence the reli...
Transformer Decoder Learns from a Pretrained Protein Language Model to Generate Ligands with High Affinity.
Journal of chemical information and modeling
Jan 27, 2025
The drug discovery process can be significantly accelerated by using deep learning methods to suggest molecules with druglike features and, more importantly, that are good candidates to bind specific proteins of interest. We present a novel deep lear...
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