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Presentation1_The Real-Time and Patient-Specific Prediction..:

Kan Wang (69396) ; Binyu Gao (12044108) ; Heqi Liu (12044111)..
https://figshare.com/articles/presentation/Presentation1_The_Real-Time_and_Patient-Specific_Prediction_for_Duration_and_Recovery_Profile_of_Cisatracurium_Based_on_Deep_Learning_Models_pdf/19120274. , 2022

Link: https://doi.org/10.3389/fphar.2021.831149.s001

RT Journal
T1 <Title>Presentation1_The Real-Time and Patient-Specific Prediction for Duration and Recovery Profile of Cisatracurium Based on Deep Learning Models.pdf</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_19120274&Exemplar=1&LAN=DE
				
A1 Kan Wang (69396)
A1 Binyu Gao (12044108)
A1 Heqi Liu (12044111)
A1 Hui Chen (28597)
A1 Honglei Liu (1538044)
YR 2022
K1 Pharmacology
K1 Basic Pharmacology
K1 Clinical Pharmacology and Therapeutics
K1 Clinical Pharmacy and Pharmacy Practice
K1 Pharmaceutical Sciences
K1 Pharmacogenomics
K1 Toxicology (incl. Clinical Toxicology)
K1 Pharmacology and Pharmaceutical Sciences not elsewhere classified
K1 deep learning–artificial neural network
K1 Long Short-Term Memory
K1 GRU (gated recurrent unit)
K1 temporal sequence analysis
K1 general anesthesia
JF https://figshare.com/articles/presentation/Presentation1_The_Real-Time_and_Patient-Specific_Prediction_for_Duration_and_Recovery_Profile_of_Cisatracurium_Based_on_Deep_Learning_Models_pdf/19120274
LK http://dx.doi.org/https://doi.org/10.3389/fphar.2021.831149.s001
DO https://doi.org/10.3389/fphar.2021.831149.s001
SF ELIB - SuUB Bremen

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