A Novel Deep Learning Approach for Automated Diagnosis of Acute Ischemic Infarction on Computed Tomography

Autor:	Ashley Knight-Greenfield, Jessica M. Peña, Tong Zhang, Peng Sun, Lohendran Baskaran, James K. Min, Ajay Gupta, Praneil Patel, Qi Chang, Kranthi K. Kolli, Ashley Beecy, Kimberly Elmore, Hao Wang, Khalil Anchouche, Hooman Kamel, Subhi J. Al'Aref
Rok vydání:	2018
Předmět:	Brain Infarction Male medicine.medical_specialty Population MEDLINE Computed tomography 030204 cardiovascular system & hematology 03 medical and health sciences Deep Learning 0302 clinical medicine Predictive Value of Tests Internal medicine Ischemic infarction medicine Humans Radiology Nuclear Medicine and imaging Prospective Studies education Prospective cohort study Stroke Aged Cause of death Aged 80 and over education.field_of_study medicine.diagnostic_test business.industry Reproducibility of Results Middle Aged medicine.disease Predictive value of tests Acute Disease Cardiology Radiographic Image Interpretation Computer-Assisted Female Tomography X-Ray Computed Cardiology and Cardiovascular Medicine business 030217 neurology & neurosurgery
Zdroj:	JACC: Cardiovascular Imaging. 11:1723-1725
ISSN:	1936-878X
Popis:	Stroke is the fourth leading cause of death and the leading cause of morbidity and long-term disability in adults [(1)][1]. Early diagnosis of acute ischemic stroke (AIS) in patients is difficult and the need for this early diagnosis will increase as the population ages and acute therapies evolve.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa809afef038273ce481022d77a4681c https://doi.org/10.1016/j.jcmg.2018.03.012 Zobrazit plný text záznamu