METHODS: A literature review of existing studies related to HIE efforts from 2005 was undertaken. Four electronic research databases (PubMed, Web of Science, CINAHL, and Academic Search Premiere) were searched for articles addressing different phases of HIE assimilation process.
RESULTS: Two hundred and fifty-four articles were initially selected. Out of 254, 44 studies met the inclusion criteria and were reviewed. The assimilation of HIE is a complicated and a multi-staged process. Our findings indicated that HIE assimilation process consisted of four main phases: initiation, organizational adoption decision, implementation and institutionalization. The data helped us recognize the assimilation pattern of HIE in healthcare organizations.
CONCLUSIONS: The results provide useful theoretical implications for research by defining HIE assimilation pattern. The findings of the study also have practical implications for policy makers. The findings show the importance of raising national awareness of HIE potential benefits, financial incentive programs, use of standard guidelines, implementation of certified technology, technical assistance, training programs and trust between healthcare providers. The study highlights deficiencies in the current policy using the literature and identifies the "pattern" as an indication for a new policy approach.
METHODS: This study followed the guidelines of the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA). A comprehensive search of online databases/search tools (Web of Science, Scopus, PubMed, Ovid, and Google Scholar) was conducted for all relevant studies published up until May 29, 2023. Only in-vitro studies comparing the adherence of Candida albicans to the digital and conventional acrylic resins were included. The quantitative analyses were performed using RevMan v5.3 software.
RESULTS: Fourteen studies were included, 11 of which were meta-analyzed based on Colony Forming Unit (CFU) and Optical Density (OD) outcome measures. The pooled data revealed significantly lower candida colonization on the milled digitally-fabricated compared to the heat-polymerized conventionally-fabricated acrylic resin materials (MD = - 0.36; 95%CI = - 0.69, - 0.03; P = 0.03 and MD = - 0.04; 95%CI = - 0.06, - 0.01; P = 0.0008; as measured by CFU and OD respectively). However, no differences were found in the adhesion of Candida albicans between the 3D-printed digitally-fabricated compared to the heat-polymerized conventionally-fabricated acrylic resin materials (CFU: P = 0.11, and OD: P = 0.20).
CONCLUSION: The available evidence suggests that candida is less likely to adhere to the milled digitally-fabricated acrylic resins compared to the conventional ones.
METHODS: To answer this demand, the Health Equity Assessment Toolkit (HEAT), was developed between 2014 and 2016. The software, which contains the World Health Organization's Health Equity Monitor database, allows the assessment of inequalities within a country using over 30 reproductive, maternal, newborn and child health indicators and five dimensions of inequality (economic status, education, place of residence, subnational region and child's sex, where applicable).
RESULTS/CONCLUSION: HEAT was beta-tested in 2015 as part of ongoing capacity building workshops on health inequality monitoring. This is the first and only application of its kind; further developments are proposed to introduce an upload data feature, translate it into different languages and increase interactivity of the software. This article will present the main features and functionalities of HEAT and discuss its relevance and use for health inequality monitoring.
METHODS: We conducted a thorough literature search using PubMed without restrictions on publication date as well as Google Scholar to manually search for other relevant articles. Abstracts were included if they described data pertaining to Leptospira spp. in rats (Rattus spp.) from any geographic region around the world, including reviews. The data extracted from the articles selected included the author(s), year of publication, geographic location, method(s) of detection used, species of rat(s), sample size, prevalence of Leptospira spp. (overall and within each rat species), and information on species, serogroups, and/or serovars of Leptospira spp. detected.
FINDINGS: A thorough search on PubMed retrieved 303 titles. After screening the articles for duplicates and inclusion/exclusion criteria, as well as manual inclusion of relevant articles, 145 articles were included in this review. Leptospira prevalence in rats varied considerably based on geographic location, with some reporting zero prevalence in countries such as Madagascar, Tanzania, and the Faroe Islands, and others reporting as high as >80% prevalence in studies done in Brazil, India, and the Philippines. The top five countries that were reported based on number of articles include India (n = 13), Malaysia (n = 9), Brazil (n = 8), Thailand (n = 7), and France (n = 6). Methods of detecting or isolating Leptospira spp. also varied among studies. Studies among different Rattus species reported a higher Leptospira prevalence in R. norvegicus. The serovar Icterohaemorrhagiae was the most prevalent serovar reported in Rattus spp. worldwide. Additionally, this literature review provided evidence for Leptospira infection in laboratory rodent colonies within controlled environments, implicating the zoonotic potential to laboratory animal caretakers.
CONCLUSIONS: Reports on global distribution of Leptospira infection in rats varies widely, with considerably high prevalence reported in many countries. This literature review emphasizes the need for enhanced surveillance programs using standardized methods for assessing Leptospira exposure or infection in rats. This review also demonstrated several weaknesses to the current methods of reporting the prevalence of Leptospira spp. in rats worldwide. As such, this necessitates a call for standardized protocols for the testing and reporting of such studies, especially pertaining to the diagnostic methods used. A deeper understanding of the ecology and epidemiology of Leptospira spp. in rats in urban environments is warranted. It is also pertinent for rat control programs to be proposed in conjunction with increased efforts for public awareness and education regarding leptospirosis transmission and prevention.
MATERIALS AND METHODS: An electronic search of the scientific literature from January 2005 to June 2016 was done using Web of Science, Dentistry & Oral Sciences Source and PubMed databases. A combination of search terms "rapid maxillary expansion", "nasal", "airway" and "breathing" were used. Studies that involved surgical or combined RME-surgical treatments and patients with craniofacial anomalies were excluded.
RESULTS: The initial screening yielded a total of 183 articles. After evaluation of the titles, abstracts and accessing the full text, a total of 20 articles fulfilled both inclusion/exclusion criteria and possessed adequate evidence to be incorporated into this review.
CONCLUSIONS: Non-surgical RME was found to improve breathing, increase nasal cavity geometry and decrease nasal airway resistance in children and adolescents.
METHODS: We first tested ten traditional machine learning algorithms, and then the three-best performing algorithms (three types of SVM) were used in the rest of the study. To improve the performance of these algorithms, a data preprocessing with normalization was carried out. Moreover, a genetic algorithm and particle swarm optimization, coupled with stratified 10-fold cross-validation, were used twice: for optimization of classifier parameters and for parallel selection of features.
RESULTS: The presented approach enhanced the performance of all traditional machine learning algorithms used in this study. We also introduced a new optimization technique called N2Genetic optimizer (a new genetic training). Our experiments demonstrated that N2Genetic-nuSVM provided the accuracy of 93.08% and F1-score of 91.51% when predicting CAD outcomes among the patients included in a well-known Z-Alizadeh Sani dataset. These results are competitive and comparable to the best results in the field.
CONCLUSIONS: We showed that machine-learning techniques optimized by the proposed approach, can lead to highly accurate models intended for both clinical and research use.