Correction: Machine learning based skin lesion segmentation method with novel borders and hair removal techniques.

[This corrects the article DOI: 10.1371/journal.pone.

Digital Imaging and Artificial Intelligence in Infantile Hemangioma: A Systematic Literature Review.

Infantile hemangioma (IH) is a vascular anomaly observed in newborns, with potential severe complications if left undetected. Consequently, researchers have turned to artificial intelligence (AI) and digital imaging (DI) methods for detection, segmentation, and assessing the treatment response in IH cases. This paper conducts a systematic literature review (SLR) following the Kitchenham framework to scrutinize the utilization of AI and digital imaging techniques in IH applications.

Experiences and lessons from using digital technology for noncommunicable disease services during the COVID-19 pandemic in the Eastern Mediterranean Region.

Background: Harnessing digital technology for health service provision is inevitable, especially after the dramatic increase in demand during the COVID-19 pandemic and the observed global disruption of health services especially for People Living with Noncommunicable Diseases (PLWNCDs).

Aims: To document and share experiences, challenges and lessons learned from the use of digital health interventions (DHIs) for noncommunicable disease (NCD) service delivery during the COVID-19 pandemic in the Eastern Mediterranean Region (EMR).

Methods: We conducted a documentary research on the use of DHIs for continuity of NCD services during the COVID-19 pandemic in EMR.

Does Social Media Enhance Rhinoplasty Desire and its Recovery Period: A Saudi Retrospective Study.

Rhinoplasty, which reconstructs the shape and size of the nose, is the most frequently performed cosmetic surgery procedure. Research indicates that social media is the leading influence motivating individuals to undergo rhinoplasty. Thus, we aimed to evaluate the effect of social media on the desire for rhinoplasty and to establish whether (and if so, how) social media enhances the recovery period after rhinoplasty.

Spectral and conductivity measurements insights on loading mechanisms of DMSO/water-kaolin complexes.

Kaolin, a naturally occurring clay mineral renowned for its distinctive properties, holds significant importance across various industries. The integration of dimethyl sulfoxide (DMSO) into kaolin matrices, both in the presence and absence of water, has been extensively explored for its potential to enhance material characteristics. Addressing debates surrounding the proposed adsorption mechanism for the type I structure of DMSO, this study undertook a comprehensive physicochemical characterization of DMSO-kaolin complexes (DMSO-KCs) derived from untreated (UnK) and HCl-treated (HK) Egyptian ore, with a focus on elucidating the loading mechanism facilitated by water.

Political Leaders' Communication Strategies during COVID-19 in Highly Infected Countries: A Scoping Review.

This scoping review maps communication strategies employed by political leaders in countries that experienced high infection rates during the COVID-19 pandemic. Using the Arksey and O'Malley scoping review framework, this study systematically explored the literature from 2019 to October 2023. The process involved identifying and selecting relevant studies, charting them, and summarizing the data from the 40 articles that met the inclusion criteria.

Systematic review and meta-analysis of the prevalence, incidence and treatment outcomes of tuberculosis in Egypt: updated overview.

Background: Tuberculosis (TB) is a major cause of morbidity and mortality globally. Understanding its epidemiology and burden is critical for targeted interventions.

Aim: To highlight the prevalence, incidence and treatment outcomes of TB in Egypt during the last 2 decades.

Six dilemmas for stakeholders inherently affecting data sharing during a zoonotic (re-)emerging infectious disease outbreak response.

Background: Timely access to outbreak related data, particularly in the early events of a spillover, is important to support evidence based control measures in response to outbreaks of zoonotic Emerging Infectious Diseases (EID). Yet, this is impeded by several barriers that need to be understood to promote timely sharing of data. Using the MERS epidemic as a model for a zoonotic EID outbreak, this study sought to provide an in-depth understanding of data sharing practices.

Awareness, Knowledge, and Attitudes Regarding Health Coaching Among Umm Al-Qura University Public Health Students.

Background: In response to the growing burden of chronic diseases on the healthcare system and in pursuit of the health sector goals of Saudi Vision 2030, the Saudi Arabian Ministry of Health implemented an initiative known as health coaching, which helps patients with chronic diseases adopt a healthier lifestyle. This study aimed to assess awareness, knowledge, and attitudes towards the initiative for health coaches among public health students at Umm Al-Qura University in Makkah, Saudi Arabia.

Methods: Data were collected using an online, cross-sectional survey between March 8, 2022 and April 4, 2022.

Measuring the relationship between body mass index and depression among Saudi adult population: A nationwide cross-sectional study.

Background: The prevalence of obesity and depression shows an accelerating trend with increased risk of morbidity and disability. The exact underlying relationship between them is unclear. We aimed to evaluate the prevalence of body mass index (BMI) and depression and their associations in a large sample of Saudi adults.

Sleep-Disordered Breathing and Its Association with Nocturnal Enuresis at the Primary Schools in Saudi Arabia: A Cross-Sectional Study.

The correlation between nocturnal enuresis (NE) and sleep-disordered breathing (SDB) was reported. We aim to determine whether there is an association between NE and SDB in children and to assess the prevalence of SDB and NE in primary school children aged 6-12 years in Saudi Arabia. A cross-sectional observational study was conducted among the caregivers of children aged 6-12 years in all Saudi Arabia regions.

Dynamics of Anti-S IgG Antibodies Titers after the Second Dose of COVID-19 Vaccines in the Manual and Craft Worker Population of Qatar.

There is limited seroepidemiological evidence on the magnitude and long-term durability of antibody titers of mRNA and non-mRNA vaccines in the Qatari population. This study was conducted to generate evidence on long-term anti-S IgG antibody titers and their dynamics in individuals who have completed a primary COVID-19 vaccination schedule. A total of 300 male participants who received any of the following vaccines BNT162b2/Comirnaty, mRNA-1273, ChAdOx1-S/Covishield, COVID-19 Vaccine Janssen/Johnson, or BBIBP-CorV or Covaxin were enrolled in our study.

Infection transmission via mobile phones in a mass gathering setting: Public knowledge, attitudes and practices in Makkah city, Saudi Arabia.

Background: Mobile phones have become part of everyday life with a potential risk for microbial transmission. Makkah is a mass gathering city that may act as hotspots of disease transmission. The contact between public and both visitors and pilgrims to Makkah can't be overlooked, and any small outbreak within the public can be transmitted rapidly to them.

Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans.

Accurate radiogenomic classification of brain tumors is important to improve the standard of diagnosis, prognosis, and treatment planning for patients with glioblastoma. In this study, we propose a novel two-stage MGMT Promoter Methylation Prediction (MGMT-PMP) system that extracts latent features fused with radiomic features predicting the genetic subtype of glioblastoma. A novel fine-tuned deep learning architecture, namely Deep Learning Radiomic Feature Extraction (DLRFE) module, is proposed for latent feature extraction that fuses the quantitative knowledge to the spatial distribution and the size of tumorous structure through radiomic features: (GLCM, HOG, and LBP).

Gender differences in prevalence of hepatitis C virus infection in Egypt: a systematic review and meta-analysis.

Egypt is the country with the highest known hepatitis C virus (HCV) prevalence worldwide. The origin of gender differences in HCV prevalence is not usually well understood. This systematic review and meta-analysis aimed to review and evaluate the gender differences in HCV infection rates amongst Egyptians.

A framework for measuring timeliness in the outbreak response path: lessons learned from the Middle East respiratory syndrome (MERS) epidemic, September 2012 to January 2019.

BackgroundEpidemics are a constant threat in the 21st century, particularly disease outbreaks following spillover of an animal virus to humans. Timeliness, a key metric in epidemic response, can be examined to identify critical steps and delays in public health action.AimTo examine timeliness, we analysed the response to the Middle East respiratory syndrome (MERS) epidemic, with a focus on the international and One Health response efforts.

Improved Bald Eagle Search Optimization with Synergic Deep Learning-Based Classification on Breast Cancer Imaging.

Medical imaging has attracted growing interest in the field of healthcare regarding breast cancer (BC). Globally, BC is a major cause of mortality amongst women. Now, the examination of histopathology images is the medical gold standard for cancer diagnoses.

Study of the Antimicrobial Potential of Actinomycetes Isolated from Organic and Inorganic Waste.

The main objective of this investigation was to characterize a collection of actinomycetes strains isolated from unexplored polluted ecosystems and to evaluate their antimicrobial potential in order to discover interesting bioactive compounds. Based on morphological and culture characters, 32 different strains were isolated: 20 strains from compost heap, seven strains from manure, and five strains from waste water. As expected, the genus Streptomyces was the most prevalent followed by the genus Micromonospora.

Stay-at-home orders during COVID-19 pandemic: an experience from general population in Damietta Governorate, Egypt.

Background: The COVID-19 pandemic in Egypt triggered national preparedness, public engagement, and an integrated response that included social distancing measures, for example, staying at home. We aimed to investigate community awareness of and commitment to complying with the stay-at-home orders in Damietta Governorate, Egypt, during the COVID-19 pandemic.

Methods: A web-based cross-sectional survey was designed and completed by 500 adult participants from Damietta, Egypt, between April 10 and July 15, 2020.

COVID-19 vaccination acceptance and trust among adults in Makkah, Saudi Arabia: a cross-sectional study.

Background: Public acceptance, trust, and actual uptake of COVID-19 vaccines are crucial to stem the pandemic. Although roll out of vaccines was high in KSA, the public response was not sufficiently studied. We aimed to investigate knowledge level, acceptance, and trust in COVID-19 vaccination and related predictors among adults in Makkah, KSA.

Triggers for Acceptance of COVID-19 Vaccination: A Community- Based Study.

Background: COVID- 19 vaccines have been released, giving a major hope of getting rid of the dark pandemic crisis. The availability of vaccines does not necessarily mean that the mass vaccination program is a success. We aimed to investigate COVID-19 vaccination knowledge level, acceptance rate, and perception state among Egyptians.

Intelligent Epileptic Seizure Detection and Classification Model Using Optimal Deep Canonical Sparse Autoencoder.

Epileptic seizures are a chronic and persistent neurological illness that mainly affects the human brain. Electroencephalogram (EEG) is considered an effective tool among neurologists to detect various brain disorders, including epilepsy, owing to its advantages, such as its low cost, simplicity, and availability. In order to reduce the severity of epileptic seizures, it is necessary to design effective techniques to identify the disease at an earlier stage.