AIMC Topic: Time Factors

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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
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...

Context Sensitive Network for weakly-supervised fine-grained temporal action localization.

Neural networks : the official journal of the International Neural Network Society
Weakly-supervised fine-grained temporal action localization seeks to identify fine-grained action instances in untrimmed videos using only video-level labels. The primary challenge in this task arises from the subtle distinctions among various fine-g...

Automated vs manual cardiac MRI planning: a single-center prospective evaluation of reliability and scan times.

European radiology
OBJECTIVES: Evaluating the impact of an AI-based automated cardiac MRI (CMR) planning software on procedure errors and scan times compared to manual planning alone.

Research on predicting radiographic exposure time in imaging based on neural network prediction models.

Clinical neurology and neurosurgery
OBJECTIVE: To explore the anatomical and clinical factors that affect the radiographic exposure time in radial artery cerebral angiography and to establish a model.

(ω,c)-Asymptotically periodic oscillation of cellular neural networks on time scales with leakage delays and mixed time-varying delays.

Neural networks : the official journal of the International Neural Network Society
In this paper, we introduce the concept of (ω,c)-asymptotic periodicity within the context of translation-invariant time scales. This concept generalizes various types of function, including asymptotically periodic, asymptotically antiperiodic, asymp...

DGMSCL: A dynamic graph mixed supervised contrastive learning approach for class imbalanced multivariate time series classification.

Neural networks : the official journal of the International Neural Network Society
In the Imbalanced Multivariate Time Series Classification (ImMTSC) task, minority-class instances typically correspond to critical events, such as system faults in power grids or abnormal health occurrences in medical monitoring. Despite being rare a...

MDWConv:CNN based on multi-scale atrous pyramid and depthwise separable convolution for long time series forecasting.

Neural networks : the official journal of the International Neural Network Society
Long time series forecasting has extensive applications in various fields such as power dispatching, traffic control, and weather forecasting. Recently, models based on the Transformer architecture have dominated the field of time series forecasting....

ABCoRT: Retention Time Prediction for Metabolite Identification via Atom-Bond Co-Learning.

Journal of chemical information and modeling
Liquid chromatography retention time (RT) prediction plays a crucial role in metabolite identification, a challenging and essential task in untargeted metabolomics. Accurate molecular representation is vital for reliable RT prediction. To address thi...

Leveraging neighborhood distance awareness for entity alignment in temporal knowledge graphs.

Neural networks : the official journal of the International Neural Network Society
Entity alignment (EA) is a typical strategy for knowledge graph integration, aiming to identify and align different entity pairs representing the same real object from different knowledge graphs. Temporal Knowledge Graph (TKG) extends the static know...