Computer-Aided Diagnosis and Clinical Trials of Cardiovascular Diseases Based on Artificial Intelligence Technologies for Risk-Early Warning Model

The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysis of medical data. In order to achieve the regional medical and public health data analysis through artificial intelligence technologies, spark data a...

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Veröffentlicht in:	Journal of medical systems Jg. 43; H. 7; S. 228 - 10
Hauptverfasser:	Li, Bin, Ding, Shuai, Song, Guolei, Li, Jiajia, Zhang, Qian
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.07.2019 Springer Nature B.V
Schlagworte:	Acute Disease Artificial Intelligence Bayes Theorem Bayesian analysis Cardiovascular diseases Chronic Disease Clinical trials Congestive heart failure Data analysis Data management Data mining Data Mining - methods Data processing Diagnosis, Computer-Assisted - methods Diagnostic systems Distributed Analytics and Deep Learning in Health Care Health Informatics Health Sciences Heart failure Heart Failure - diagnosis Humans Hypertension Illnesses Intelligence (information) Logistic Models Medical diagnosis Medical research Medicine Medicine & Public Health Optimization Prognosis Public health Redundancy Regional analysis Regression analysis Renal failure Renal Insufficiency - diagnosis Risk Assessment Severity of Illness Index Signs and symptoms Statistics for Life Sciences Stroke - diagnosis Support Vector Machine Support vector machines Systems-Level Quality Improvement Naive Bayesian regression Clinical feature Artificial Intelligence Z-score standard Chronic cardiovascular disease Support vector machine Logistic
ISSN:	0148-5598, 1573-689X, 1573-689X
Online-Zugang:	Volltext
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