http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-114171203-A

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filingDate 2021-11-29-04:00^^<http://www.w3.org/2001/XMLSchema#date>
inventor http://rdf.ncbi.nlm.nih.gov/pubchem/patentinventor/MD5_b1e905468e034648777f6f817683ffad
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publicationDate 2022-03-11-04:00^^<http://www.w3.org/2001/XMLSchema#date>
publicationNumber CN-114171203-A
titleOfInvention Prediction method and system of cardiac arrest animal model based on deep learning based on behavioral features
abstract The invention discloses a method and a system for predicting a cardiac arrest animal model based on deep learning based on behavior characteristics, which is applied to the technical fields of machine learning and medical model construction, and includes the following steps: a data acquisition step, a data preprocessing step, a matrix construction step, and a data division step , gradient extraction step, 3D‑CNN network training step, training end judgment step, cardiac arrest animal model prediction step. According to the requirements of cardiac arrest induction and resuscitation, the invention realizes the prediction of the cardiac arrest animal model, with high prediction accuracy, low average relative error and root mean square error; the obtained cardiac arrest animal model has high resuscitation success rate, The reproducible and stable large animal swine model of traumatic cardiac arrest with obvious damage to important organs and relatively long survival time creates good model conditions for domestic and foreign counterparts to conduct basic and preclinical research on traumatic cardiac arrest.
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