Background: The recent global outbreak of coronavirus disease (COVID-19) is affecting many countries worldwide. Iran is one of the top 10 most affected countries. Search engines provide useful data from populations, and these data might be useful to analyze epidemics. Utilizing data mining methods on electronic resources’ data might provide a better insight into the COVID-19 outbreak to manage the health crisis in each country and worldwide. Objective: This study aimed to predict the incidence of COVID-19 in Iran. Methods: Data were obtained from the Google Trends website. Linear regression and long short-term memory (LSTM) models were used to estimate the number of positive COVID-19 cases. All models were evaluated using 10-fold cross-validation, and root mean square error (RMSE) was used as the performance metric. Results: The linear regression model predicted the incidence with an RMSE of 7.562 (SD 6.492). The most effective factors besides previous day incidence included the search frequency of handwashing, hand sanitizer, and antiseptic topics. The RMSE of the LSTM model was 27.187 (SD 20.705). Conclusions: Data mining algorithms can be employed to predict trends of outbreaks. This prediction might support policymakers and health care managers to plan and allocate health care resources accordingly.

Metal-organic frameworks (MOFs) are a fascinating class of crystalline porous materials composed of metal ions and organic ligands. Due to their attractive properties, MOFs can potentially offer biomedical field applications, such as drug delivery and imaging. This study aimed to systematically identify the affecting factors on the MOF characteristics and their effects on structural and biological characteristics. An electronic search was performed in four databases containing PubMed, Scopus, Web of Science, and Embase, using the relevant keywords. After analyzing the studies, 20 eligible studies were included in this review. As a result, various factors such as additives and organic ligand can influence the size and structure of MOFs. Additives are materials that can compete with ligand and may affect the nucleation and growth processes and, consequently, particle size. The nature and structure of ligand are influential in determining the size and structure of MOF. Moreover, synthesis parameters like the reaction time and initial reagents ratio are critical factors that should be optimized to regulate the size and structure. Of note is that the nature of the ligand and using a suitable additive can control the porosity of MOF. The more extended ligands aid in forming large pores. The choice of metallic nodes and organic ligand, and the MOF concentration are important factors since they can determine toxicity and biocompatibility of the final structure. The physicochemical properties of MOFs, such as hydrophobicity, affect the toxicity of nanoparticles. An increase in hydrophobicity causes increased toxicity of MOF. The biodegradability of MOF, as another property, depends on the organic ligand and metal ion and environmental conditions like pH. Photocleavable ligands can be served for controlled degradation of MOFs. Generally, by optimizing these affecting factors, MOFs with desirable properties will be obtained for biomedical applications.

Objectives: Despite the growing use of mobile health (mHealth), certain barriers seem to be hindering the use of mHealth applications in healthcare. This article presents a systematic review of the literature on barriers associated with mHealth reported by healthcare professionals.Methods: This systematic review was carried out to identify studies published from January 2015 to December 2019 by searching four electronic databases (PubMed/MEDLINE, Web of Science, Embase, and Google Scholar). Studies were included if they reported perceived barriers to the adoption of mHealth from healthcare providers’ perspectives. Content analysis and categorization of barriers were performed based on a focus group discussion that explored researchers’ knowledge and experiences.Results: Among the 273 papers retrieved through the search strategy, 18 works were selected and 18 barriers were identified. The relevant barriers were categorized into three main groups: technical, individual, and healthcare system. Security and privacy concerns from the category of technical barriers, knowledge and limited literacy from the category of individual barriers, and economic and financial factors from the category of healthcare system barriers were chosen as three of the most important challenges related to the adoption of mHealth described in the included publications.Conclusions: mHealth adoption is a complex and multi-dimensional process that is widely implemented to increase access to healthcare services. However, it is influenced by various factors and barriers. Understanding the barriers to adoption of mHealth applications among providers, and engaging them in the adoption process will be important for the successful deployment of these applications.

Background: COVID-19, the disease caused by the novel coronavirus SARS-CoV-2, has become a global pandemic, affecting most countries worldwide. Digital health information technologies can be applied in three aspects, namely digital patients, digital devices, and digital clinics, and could be useful in fighting the COVID-19 pandemic. Objective: Recent reviews have examined the role of digital health in controlling COVID-19 to identify the potential of digital health interventions to fight the disease. However, this study aims to review and analyze the digital technology that is being applied to control the COVID-19 pandemic in the 10 countries with the highest prevalence of the disease. Methods: For this review, the Google Scholar, PubMed, Web of Science, and Scopus databases were searched in August 2020 to retrieve publications from December 2019 to March 15, 2020. Furthermore, the Google search engine was used to identify additional applications of digital health for COVID-19 pandemic control. Results: We included 32 papers in this review that reported 37 digital health applications for COVID-19 control. The most common digital health projects to address COVID-19 were telemedicine visits (11/37, 30%). Digital learning packages for informing people about the disease, geographic information systems and quick response code applications for real-time case tracking, and cloud- or mobile-based systems for self-care and patient tracking were in the second rank of digital tool applications (all 7/37, 19%). The projects were deployed in various European countries and in the United States, Australia, and China. Conclusions: Considering the potential of available information technologies worldwide in the 21st century, particularly in developed countries, it appears that more digital health products with a higher level of intelligence capability remain to be applied for the management of pandemics and health-related crises.

A Systematic Review of Nutrition Recommendation Systems: With Focus on Technical Aspects