Clinical artificial intelligence quality improvement: towards continual monitoring and updating of AI algorithms in healthcare
Abstract Machine learning (ML) and artificial intelligence (AI) algorithms have the potential to
derive insights from clinical data and improve patient outcomes. However, these highly …
derive insights from clinical data and improve patient outcomes. However, these highly …
Overview of PCA-based statistical process-monitoring methods for time-dependent, high-dimensional data
High-dimensional and time-dependent data pose significant challenges to statistical process
monitoring. Dynamic principal-component analysis, recursive principal-component analysis …
monitoring. Dynamic principal-component analysis, recursive principal-component analysis …
[图书][B] Introduction to statistical process control
P Qiu - 2013 - books.google.com
A major tool for quality control and management, statistical process control (SPC) monitors
sequential processes, such as production lines and Internet traffic, to ensure that they work …
sequential processes, such as production lines and Internet traffic, to ensure that they work …
[图书][B] Risk, surprises and black swans: fundamental ideas and concepts in risk assessment and risk management
T Aven - 2014 - taylorfrancis.com
Risk, Surprises and Black Swans provides an in depth analysis of the risk concept with a
focus on the critical link to knowledge; and the lack of knowledge, that risk and probability …
focus on the critical link to knowledge; and the lack of knowledge, that risk and probability …
Some current directions in the theory and application of statistical process monitoring
WH Woodall, DC Montgomery - Journal of Quality Technology, 2014 - Taylor & Francis
The purpose of this paper is to provide an overview and our perspective of recent research
and applications of statistical process monitoring. The focus is on work done over the past …
and applications of statistical process monitoring. The focus is on work done over the past …
Augmented time regularized generative adversarial network (atr-gan) for data augmentation in online process anomaly detection
Supervised machine learning techniques, such as classification models, have been widely
applied to online process anomaly detection in advanced manufacturing. However, since …
applied to online process anomaly detection in advanced manufacturing. However, since …
A new method of dynamic latent-variable modeling for process monitoring
Dynamic principal component analysis (DPCA) is widely used in the monitoring of dynamic
multivariate processes. In traditional DPCA where a time window is used, the dynamic …
multivariate processes. In traditional DPCA where a time window is used, the dynamic …
[图书][B] Unsupervised process monitoring and fault diagnosis with machine learning methods
Although this book is focused on the process industries, the methodologies discussed in the
following chapters are generic and can in many instances be applied with little modification …
following chapters are generic and can in many instances be applied with little modification …
[PDF][PDF] 工业过程异常检测, 寿命预测与维修决策的研究进展
周东华， 魏慕恒， 司小胜 - 自动化学报, 2013 - aas.net.cn
摘要作为保障工业过程安全性, 可靠性和经济性的重要技术, 异常检测, 寿命预测与维修决策在
过去几十年得到了越来越广泛的关注和长足的发展. 本文结合异常检测, 寿命预测与维修决策各 …
过去几十年得到了越来越广泛的关注和长足的发展. 本文结合异常检测, 寿命预测与维修决策各 …
A perspective on PSE in pharmaceutical process development and innovation
KV Gernaey, AE Cervera-Padrell… - Computers & chemical …, 2012 - Elsevier
The pharmaceutical industry is under growing pressure to increase efficiency, both in
production and in process development. This paper discusses the central role of Process …
production and in process development. This paper discusses the central role of Process …