Publications by authors named "B Hosseini"

Introduction: While several studies have examined stroke public knowledge and awareness in individual countries within the Middle East and North Africa (MENA) region, none have provided a comprehensive cross-country assessment.

Purpose: To assess public stroke knowledge and awareness among Arabic-speaking adults in seven MENA countries and identify associated factors.

Materials And Methods: An online cross-sectional survey was self-administered by the public population in Iraq, Lebanon, Sudan, Jordan, United Arab Emirates, Syria, and Saudi Arabia (April 2021-2023).

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(anamorph: ) species are endophytes or fungal pathogens for many different plant species. Soybean () can be infected by many different species; among them, and are responsible for the most significant damages. is a species that was only recently described and has so far been found on sunflower () in Australia and an unknown host in Thailand.

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Background: Early warning systems (EWSs) are tools that integrate clinical observations to identify patterns indicating increased risks of clinical deterioration, thus facilitating timely and appropriate interventions. EWSs can mitigate the impact of global infectious diseases by enhancing information exchange, monitoring, and early detection.

Objective: We aimed to evaluate the effectiveness of EWSs in acute respiratory infections (ARIs) through a scoping review of EWSs developed, described, and implemented for detecting novel, exotic, and re-emerging ARIs.

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Article Synopsis
  • The study evaluated medication adherence among Jordanian patients with dyslipidemia and examined how factors like health literacy, well-being, and doctor-patient communication affect adherence.
  • Conducted from March to July 2023, the research involved 410 adults at a tertiary hospital, using several validated scales to gather data on adherence and related variables.
  • Results indicated that older age, higher education, prior surgery, and better communication improved adherence, while smoking and lack of health insurance negatively impacted it, highlighting the need for interventions to enhance adherence.
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Background: The integration of machine learning (ML) in predicting asthma-related outcomes in children presents a novel approach in pediatric health care.

Objective: This scoping review aims to analyze studies published since 2019, focusing on ML algorithms, their applications, and predictive performances.

Methods: We searched Ovid MEDLINE ALL and Embase on Ovid, the Cochrane Library (Wiley), CINAHL (EBSCO), and Web of Science (core collection).

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