Publications by authors named "P Perdikaris"

Operator learning is a rising field of scientific computing where inputs or outputs of a machine learning model are functions defined in infinite-dimensional spaces. In this paper, we introduce Neon (Neural Epistemic Operator Networks), an architecture for generating predictions with uncertainty using a single operator network backbone, which presents orders of magnitude less trainable parameters than deep ensembles of comparable performance. We showcase the utility of this method for sequential decision-making by examining the problem of composite Bayesian Optimization (BO), where we aim to optimize a function , where is an unknown map which outputs elements of a function space, and is a known and cheap-to-compute functional.

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Article Synopsis
  • Oral mucositis (OM) is a serious side effect of cancer treatments in children, affecting up to 91.5% of pediatric patients and significantly impacting their quality of life.
  • A systematic review of randomized controlled trials from 2000 to 2023 identified 34 studies, with five focusing on Low Level Laser Therapy (LLLT) and honey, which were included in the meta-analysis.
  • The results showed that honey can reduce hospital stay duration for severe OM, while LLLT was ineffective in preventing or treating moderate to severe OM, indicating that honey may be a promising treatment option for managing OM in children.
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Background: With its abrupt and huge health and socio-economic consequences, the coronavirus disease (COVID-19) pandemic has led to a uniquely demanding, intensely stressful, and even traumatic period. Healthcare workers (HCW), especially nurses, were exposed to mental health challenges during those challenging times.

Objectives: Review the current literature on mental health problems among nurses caring for COVID-19 patients.

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Recently, deep learning surrogates and neural operators have shown promise in solving partial differential equations  (PDEs). However, they often require a large amount of training data and are limited to bounded domains. In this work, we present a novel physics-informed neural operator method to solve parameterized boundary value problems without labeled data.

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During the COVID-19 pandemic, numerous studies have shown the high prevalence of occupational stress (OS) of health workers, affecting the quality of health care provided. To date, there is no study regarding OS of emergency care pediatric nurses working in Greece. This study aimed to examine the pediatric nurses' OS working in tertiary public hospitals in Greece.

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