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Published in 2022 at "Cancer Cytopathology"
DOI: 10.1002/cncy.22669
Abstract: Several studies have used artificial intelligence (AI) to analyze cytology images, but AI has yet to be adopted in clinical practice. The objective of this study was to demonstrate the accuracy of AIābased image analysis…
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Keywords:
application;
ancillary diagnostic;
application deep;
deep learning ... See more keywords
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Published in 2020 at "Science China Earth Sciences"
DOI: 10.1007/s11430-019-9584-9
Abstract: Ecological resources are an important material foundation for the survival, development, and self-realization of human beings. In-depth and comprehensive research and understanding of ecological resources are beneficial for the sustainable development of human society. Advances…
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Keywords:
resource research;
ecological resource;
deep learning;
application deep ... See more keywords
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Published in 2021 at "International journal of cardiology"
DOI: 10.1016/j.ijcard.2021.05.017
Abstract: Electrocardiogram (ECG) is a commonly-used, non-invasive examination recording cardiac voltage versus time traces over a period. Deep learning technology, a robust artificial intelligence algorithm, can imitate the data processing patterns of the human brain, and…
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Keywords:
learning electrocardiogram;
electrocardiogram came;
deep learning;
application deep ... See more keywords
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Published in 2025 at "Journal of Chemical Information and Modeling"
DOI: 10.1021/acs.jcim.4c02293
Abstract: This study investigates the application of a deep learning (DL) model, specifically a message-passing neural network (MPNN) implemented through Chemprop, to predict the persistence, bioaccumulation, and toxicity (PBT) characteristics of compounds, with a focus on…
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Keywords:
deep learning;
application deep;
persistence bioaccumulation;
bioaccumulation toxicity ... See more keywords
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Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-88936-y
Abstract: Psidium guajava L. is an important tropical and subtropical fruit. Due to its geographical location and suitable climate, Taiwan produces Psidium guajava L. all year round. Quality standardization is therefore a crucial issue. The primary…
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deep learning;
application deep;
psidium;
fruit ... See more keywords
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Published in 2021 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbaa043
Abstract: The increase in biological data and the formation of various biomolecule interaction databases enable us to obtain diverse biological networks. These biological networks provide a wealth of raw materials for further understanding of biological systems,…
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Keywords:
network;
biological networks;
deep learning;
learning methods ... See more keywords
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Published in 2025 at "International Journal of Low-Carbon Technologies"
DOI: 10.1093/ijlct/ctae290
Abstract: This study proposes a deep learning-based framework to improve the efficiency and sustainability of LCSCM. Firstly, a multi-scale time series decomposition LSTM (MS-TDLSTM) model is proposed, which combines empirical mode decomposition (EMD) and attention mechanism…
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Keywords:
deep learning;
application deep;
low carbon;
learning low ... See more keywords
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Published in 2020 at "PLoS ONE"
DOI: 10.1371/journal.pone.0235447
Abstract: Objective To explore the application of deep neural networks (DNNs) and deep reinforcement learning (DRL) in wireless communication and accelerate the development of the wireless communication industry. Method This study proposes a simple cognitive radio…
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Keywords:
deep neural;
communication;
power;
rate ... See more keywords
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Published in 2022 at "European journal of medicinal chemistry"
DOI: 10.2139/ssrn.4263815
Abstract: The deep conditional transformer neural network SyntaLinker was applied to identify compounds with pyrrolo[2,3-d]pyrimidine scaffold as potent selective TBK1 inhibitor. Further medicinal chemistry optimization campaign led to the discovery of the most potent compound 7l,…
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Keywords:
tbk1;
chemistry;
pyrrolo pyrimidine;
application deep ... See more keywords
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Published in 2023 at "Studies in health technology and informatics"
DOI: 10.3233/shti230325
Abstract: Deep learning models for radiology are typically deployed either through cloud-based platforms, through on-premises infrastructures, or though heavyweight viewers. This tends to restrict the audience of deep learning models to radiologists working in state-of-the-art hospitals,…
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Keywords:
client side;
learning models;
application deep;
deep learning ... See more keywords
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Published in 2022 at "Frontiers in Neurorobotics"
DOI: 10.3389/fnbot.2022.829445
Abstract: Sports videos are blowing up over the internet with enriching material life and the higher pursuit of spiritual life of people. Thus, automatically identifying and detecting helpful information from videos have arisen as a relatively…
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Keywords:
network;
hpe model;
sports videos;
application deep ... See more keywords