Utilization of Oral Healthcare Among Uninsured Populations During the COVID-19 Pandemic in the United States.

Background: Accessibility to dental care is vital for uninsured low-income individuals. There is a deficit of research that examines oral healthcare seeking during the COVID-19 pandemic among uninsured low-income individuals. The purpose of this study is to describe oral health-related issues among patients of a free clinic that does not provide dental care during the COVID-19 pandemic.

Health Information Needs of Breast Cancer Survivors: An Umbrella Review.

Purpose: The aim of this umbrella review was to identify the main information needs of breast cancer survivors. Since several reviews have already been done on this topic, conducting an umbrella review not only combines their results but also gives a comprehensive picture and informative summary of breast cancer survivors' needs.

Method: The search was performed in PubMed, Embase, Scopus, Web of Science, ProQuest, Cochrane, and Google Scholar from inception to the end of March 2024.

Assessment of thyroid dose in orthopantomogram imaging with different thyroid shield materials: a Monte Carlo simulation study.

Radiation protection in dental radiography can be achieved by adjusting the image field size, exposure, and filtration parameters, and using protective lead shields. The aim of this study is to assess the radiation dose delivered to the thyroid in a phantom irradiated by an orthopantomogram (OPG) system using Geant4 simulation toolkit. Recently, researchers have been trying to find an alternative material to the lead thyroid shield so that the OPG image has minimal metal artifacts.

Adaptive network approach to exploration-exploitation trade-off in reinforcement learning.

A foundational machine-learning architecture is reinforcement learning, where an outstanding problem is achieving an optimal balance between exploration and exploitation. Specifically, exploration enables the agents to discover optimal policies in unknown domains of the environment for gaining potentially large future rewards, while exploitation relies on the already acquired knowledge to maximize the immediate rewards. We articulate an approach to this problem, treating the dynamical process of reinforcement learning as a Markov decision process that can be modeled as a nondeterministic finite automaton and defining a subset of states in the automaton to represent the preference for exploring unknown domains of the environment.

Iranian experts' perspectives on facilitators and barriers influencing the infectious disease knowledge network: A qualitative study.

Background: Knowledge networks, such as Communities of Practice (CoP), are essential elements of knowledge management. They play a crucial role in assimilating various knowledge domains and converting individual knowledge into collective knowledge. This study aimed to assess the concept of knowledge networks and identify facilitators and barriers influencing knowledge sharing in infectious diseases, according to Iranian experts.