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This article was published in the following journal.
Name: Annals of surgical oncology
Multiple clinical trials support the effectiveness of cardiac resynchronization therapy (CRT); however, optimal patient selection remains challenging due to substantial treatment heterogeneity among p...
Machine learning develops rapidly, which has made many theoretical breakthroughs and is widely applied in various fields. Optimization, as an important part of machine learning, has attracted much att...
Systems metabolic engineering allows efficient development of high performing microbial strains for the sustainable production of chemicals and materials. In recent years, increasing availability of b...
Early diagnosis and treatment are the most important strategies to prevent deaths from several diseases. In this regard, data mining and machine learning techniques have been useful tools to help mini...
The investigators propose to develop and evaluate a hospital department-specific machine learning based clinical decision support (CDS) system for early sepsis prediction, focused on impro...
The Hamlet.rt study is a prospective data collection and patient questionnaire study for patients undergoing image-guided radiotherapy with curative intent. The aim of the study is to use...
Machine learning methods potentially provide a highly accurate and detailed assessment of expected individual patient risk before elective cardiac surgery. Correct anticipation of this ris...
Prospective interventional study, open, non-comparative and non-randomized. The research concerns physiological parameters of the coronary and ocular blood circulation. At the coronary le...
The objective of this study is the development of a system that will allow for the precise measurement of movement kinematics in a clinical exam setting using natural video from three came...
Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.
SUPERVISED MACHINE LEARNING algorithm which learns to assign labels to objects from a set of training examples. Examples are learning to recognize fraudulent credit card activity by examining hundreds or thousands of fraudulent and non-fraudulent credit card activity, or learning to make disease diagnosis or prognosis based on automatic classification of microarray gene expression profiles drawn from hundreds or thousands of samples.
A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data.
Track and monitor developments in breast cancer research and commercial development. Follow the tabs above to read the latest global news, research, clinical trials on breast cancer and follow companies active in the development of breast cancer tr...