… While breakthroughs in machine learning and artificial intelligence are changing society, …
In this work, we show how classical theory and modern practice can be reconciled within a …

… -driven methods—machine learning and pattern recognition … this scoping of explainable
machine learning as XAI in the … ” to mean the underlying machine learning technique such as …

… In this Review, we describe the principles of data integration, and provide a taxonomy of
machine learning methods presently in use to integrate biomedical data. We discuss current …

… Recent progress in machine learning has been driven both by the development of new learning
… of these demands on recent work in machine-learning algorithms, theory, and practice. …

… application and deployment of machine learning can we identify in practice? For answering
… between challenges identified with the interviews in practice and the results from literature. …

… invite the use of machine learning algorithms into optimizing … The ability of machine learning
algorithms to learn from … and efficacy of radiotherapy practice leading to better outcomes. …

… If we understand machine learning as a data practice that reconfigures local centers of
power and knowledge by redrawing human–machine relations, then differences …

… machine learning … Machine learning includes a broad class of computer programs that
improve with experience. The complexity of creating, training, and monitoring machine learning …

… system at the Tufts Evidence-based Practice Center. More … machine learning methods.
The main aim of this work is to provide a case study in deploying cutting-edge machine learning …

… privacy mechanisms for machine learning to understand the … to a wide class of machine
learning algorithms including … methods for modifying machine learning algorithms to satisfy …