Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic
knowledge and provides expedited solutions to complex challenges. Remarkable …

In this article we introduce the concept of inverse probability of treatment weighting (IPTW)
and describe how this method can be applied to adjust for measured confounding in …

The interdisciplinary field of knowledge discovery and data mining emerged from a
necessity of big data requiring new analytical methods beyond the traditional statistical …

The complexity and dynamics of the environment make it extremely difficult to directly predict
and trace the temporal and spatial changes in pollution. In the past decade, the …

Abstract Machine learning is a branch of computer science that has the potential to transform
epidemiologic sciences. Amid a growing focus on “Big Data,” it offers epidemiologists new …

Industry 4.0 is the new industrial revolution. By connecting every machine and activity
through network sensors to the Internet, a huge amount of data is generated. Machine …

Propensity score matching (PSM) is a popular method in clinical researches to create a
balanced covariate distribution between treated and untreated groups. However, the …

The energy sector is enduring a momentous transformation with new technological
advancements and increasing demand leading to innovative pathways. Artificial intelligence …

We study deep neural networks and their use in semiparametric inference. We establish
novel nonasymptotic high probability bounds for deep feedforward neural nets. These …

Deep learning takes advantage of large datasets and computationally efficient training
algorithms to outperform other approaches at various machine learning tasks. However …