A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A binary classification problem is one where the goal is to predict the value ...

Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained model must be easily interpretable, but often don't work well with large ...

传统疾病分类模型存在决策过程缺乏透明度、未考虑误诊临床意义等问题。研究人员开展基于分层原型决策树（HPDT）的皮肤病变分类研究。结果显示 HPDT 在多方面优于现有方法，为临床决策支持提供了新途径。 在医疗影像诊断领域，随着深度学习的发展和大量 ...

Frank B¼chner of Hitex Development Tools describes how the classifications tree method can be used to transform a problem specification to a set of test case specifications. Testing is a compulsory ...

Discover how random forests, a machine-learning technique, enhance prediction accuracy by combining insights from multiple decision trees.

Clinical Relevance of Noncoding Adenosine-to-Inosine RNA Editing in Multiple Human Cancers In total, 60 CDTs were necessary to cover the whole guideline and were driven by 114 data items. Data items ...

Morbidity After Sentinel Lymph Node Biopsy in Primary Breast Cancer: Results From a Randomized Controlled Trial Data were uniformly collected on 1,433 referred men with a serum prostate-specific ...