Expression of Concern: Wang, C., Zhang, Q., Liu, W., Liu, Y. & Miao, L. Facial feature discovery for ethnicity recognition. WIREs Data Mining Knowl. Discov. 9, e1278 (2019). https://doi.org/10.1002/widm.1278 This Expression of Concern is for the above article, published online on August 2, 2018 in Wiley Online Library (wileyonlinelibrary.com), and has been published by agreement between the journal

Wiley received notification of concern about whether the ethical requirements for human subject research were met in a study by Wang, C. and colleagues that was published in WIREs Data Mining Knowledge Discovery (Wang et al., 2019) on August 2, 2018. Study participants are reported to be from ethnic or religious minority groups, with some considered part of a vulnerable population. Wiley and the WIREs

Healthcare 4.0 is a term that has emerged recently and derived from Industry 4.0. Today, the health care sector is more digital than in past decades; for example, spreading from x‐rays and magnetic resonance imaging to computed tomography and ultrasound scans to electric medical records. With the wide spectrum of digital technologies underpinning Healthcare 4.0 to deliver more effective and efficient

Many news outlets allow users to contribute comments on topics about daily world events. News articles are the seeds that spring users' interest to contribute content, that is, comments. A news outlet may allow users to contribute comments on all their articles or a selected number of them. The topic of an article may lead to an apathetic user commenting activity (several tens of comments) or to a

Algorithmic differentiation (AD), also known as automatic differentiation, is a technology for accurate and efficient evaluation of derivatives of a function given as a computer model. The evaluations of such models are essential building blocks in numerous scientific computing and data analysis applications, including optimization, parameter identification, sensitivity analysis, uncertainty quantification

The increasing computational power and proliferation of big data are now empowering Artificial Intelligence (AI) to achieve massive adoption and applicability in many fields. The lack of explanation when it comes to the decisions made by today's AI algorithms is a major drawback in critical decision‐making systems. For example, deep learning does not offer control or reasoning over its internal processes

The ring main unit (RMU) is the main equipment of the electrical power distribution network. The deterioration process of the RMU cable joint is multivariable and nonstationary over time. Existing fault detection models for the RMU cable joint are single‐variable and static over time. A novel algorithm of adaptive time neighborhood preserving embedding (ATNPE) is proposed in this paper, a multivariable

Players in the telecommunications sector struggle against the competition to keep customers, and therefore they need effective churn management. Most classification algorithms either ignore misclassification cost or assume that the costs of all incorrect classification errors are equal. But as in real life, many classification problems have different misclassification costs and this difference cannot