MP67-12 ANTI-ANDROGENS AND CABAZITAXEL IN DEFINING COMPLETE RESPONSE IN PROSTATECTOMY (ACDC TRIAL) (ACDC-RP)
نویسندگان
چکیده
منابع مشابه
ACDC: An Algorithm for Comprehension-Driven Clustering
The software clustering literature contains many diierent approaches that attempt to automatically decompose software systems. These approaches commonly utilize criteria or measures based on principles such as high cohesion and low coupling, information hiding etc. In this paper, we present an algorithm that subscribes to a philosophy targeted towards program comprehension and based on subsyste...
متن کاملACDC: A Structured Efficient Linear Layer
The linear layer is one of the most pervasive modules in deep learning representations. However, it requiresO(N) parameters andO(N) operations. These costs can be prohibitive in mobile applications or prevent scaling in many domains. Here, we introduce a deep, differentiable, fully-connected neural network module composed of diagonal matrices of parameters, A and D, and the discrete cosine tran...
متن کاملACDC: Altering Control Dependence Chains for Automated Patch Generation
Once a failure is observed, the primary concern of the developer is to identify what caused it in order to repair the code that induced the incorrect behavior. Until a permanent repair is afforded, code repair patches are invaluable. The aim of this work is to devise an automated patch generation technique that proceeds as follows: Step1) It identifies a set of failure-causing control dependenc...
متن کاملACDC: $\alpha$-Carving Decision Chain for Risk Stratification
In many healthcare settings, intuitive decision rules for risk stratification can help effective hospital resource allocation. This paper introduces a novel variant of decision tree algorithms that produces a chain of decisions, not a general tree. Our algorithm, α-Carving Decision Chain (ACDC), sequentially carves out “pure” subsets of the majority class examples. The resulting chain of decisi...
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ژورنال
عنوان ژورنال: Journal of Urology
سال: 2020
ISSN: 0022-5347,1527-3792
DOI: 10.1097/ju.0000000000000947.012