The promise of machine learning models in cardiovascular risk prediction : Machine learning predictions of the adverse events of different treatments in patients with ischemic left ventricular systolic dysfunction.

IF 3.2 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Andrea Cardona
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引用次数: 0
机器学习模型在心血管风险预测中的前景:机器学习对缺血性左心室收缩功能障碍患者不同治疗方法不良事件的预测。
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来源期刊
Internal and Emergency Medicine
Internal and Emergency Medicine 医学-医学:内科
CiteScore
7.20
自引率
4.30%
发文量
258
审稿时长
6-12 weeks
期刊介绍: Internal and Emergency Medicine (IEM) is an independent, international, English-language, peer-reviewed journal designed for internists and emergency physicians. IEM publishes a variety of manuscript types including Original investigations, Review articles, Letters to the Editor, Editorials and Commentaries. Occasionally IEM accepts unsolicited Reviews, Commentaries or Editorials. The journal is divided into three sections, i.e., Internal Medicine, Emergency Medicine and Clinical Evidence and Health Technology Assessment, with three separate editorial boards. In the Internal Medicine section, invited Case records and Physical examinations, devoted to underlining the role of a clinical approach in selected clinical cases, are also published. The Emergency Medicine section will include a Morbidity and Mortality Report and an Airway Forum concerning the management of difficult airway problems. As far as Critical Care is becoming an integral part of Emergency Medicine, a new sub-section will report the literature that concerns the interface not only for the care of the critical patient in the Emergency Department, but also in the Intensive Care Unit. Finally, in the Clinical Evidence and Health Technology Assessment section brief discussions of topics of evidence-based medicine (Cochrane’s corner) and Research updates are published. IEM encourages letters of rebuttal and criticism of published articles. Topics of interest include all subjects that relate to the science and practice of Internal and Emergency Medicine.
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