Attitudes, Awareness, and Willingness of Iranians Toward Using Telemedicine in Post-COVID Era: A Cross-Sectional Study.

Background And Aims: With the increased use of telemedicine during the pandemic, understanding patients' attitudes and readiness to adopt telemedicine is crucial. This study investigates the attitudes, willingness, and usage behaviors of Iranian patients toward telemedicine.

Methods: This cross-sectional study took place in Iran from October 2021 to January 2023.

The relationship of COVID-19 severity with laboratory findings and neutrophil-to-lymphocyte ratio in patients admitted to a large teaching hospital in Iran: A cross-sectional study.

Background And Aims: COVID-19 patients might be admitted to the hospital based on their clinical manifestations or to the intensive care unit (ICU) due to the severity of their symptoms or critical situation. Our main objective was to investigate clinical and demographic factors influencing COVID-19 patients' admission to the ICU and length of stay (LOS) using extracted data from the hospital information systems in Iran.

Methods: The data of hospitalized patients with confirmed COVID-19 were retrieved from the health information system of Imam Khomeini Hospital Complex, Tehran, Iran between March 2020 and February 2022.

Conceptual framework for establishing twins prevention and continuous health promotion programme: a qualitative study.

Background: Twin registries and cohorts face numerous challenges, including significant resource allocation, twins' recruitment and retention. This study aimed to assess expert feedback on a proposed pragmatic idea for launching a continuous health promotion and prevention programme (HPPP) to establish and maintain twin cohorts.

Design: A qualitative study incorporating an inductive thematic analysis.

Concordance between ARISCAT risk score and cardiopulmonary exercise test values in risk prediction of postoperative pulmonary complications of major abdominal surgeries in a tertiary cancer hospital: A cross-sectional study.

Background And Aims: Pulmonary complications are common after surgery. They include vascular thrombosis, pneumonia, respiratory failure (RF), and pain-related atelectasis. There are a number of models to predict the risk of postoperative respiratory events other than thrombosis.

Design and evaluation of a Mobile-Based decision support system to enhance lung transplant candidate assessment and management: knowledge translation integrated with clinical workflow.

Background: Accurate and timely decision-making in lung transplantation (LTx) programs is critical. The main objective of this study was to develop a mobile-based evidence-based clinical decision support system (CDSS) to enhance the management of lung transplant candidates.

Method: An iterative participatory software development process was employed to develop the ImamLTx CDSS.

Requirements, Challenges, and Key Components to Improve Onboard Medical Care Using Maritime Telemedicine: Narrative Review.

Introduction: Telemedicine has been able to bring healthcare services to all people in far locations such as the sea. Our main objective was to overview the main features, challenges, and requirements of applying telemedicine at sea.

Methods: The electronic search includes all types of papers published in English.

Feasibility study and determination of prerequisites of telecare programme to enhance patient management in lung transplantation: a qualitative study from the perspective of Iranian healthcare providers.

Background: Non-adherence to treatment plans, follow-up visits and healthcare advice is a common obstacle in the management of lung transplant patients. This study aims to investigate experts' views on the needs and main aspects of telecare programmes for lung transplantation.

Design: A qualitative study incorporating an inductive thematic analysis.

The Application of Knowledge-Based Clinical Decision Support Systems to Enhance Adherence to Evidence-Based Medicine in Chronic Disease.

Among the technology-based solutions, clinical decision support systems (CDSSs) have the ability to keep up with clinicians with the latest evidence in a smart way. Hence, the main objective of our study was to investigate the applicability and characteristics of CDSSs regarding chronic disease. The Web of Science, Scopus, OVID, and PubMed databases were searched using keywords from January 2000 to February 2023.

Iranian school-aged twin registry: preliminary reports and project progress.

Background: National Persian school-aged twin registry was established to provide a platform for twin studies. In this report, we describe defining registry characteristics, database design, and preliminary results regarding gathered data in the first phase of the registry program.

Method: Through focus group discussions, the required data elements to design the database and data collection process were defined.

Prediction of COVID-19 Patients' Survival by Deep Learning Approaches.

Despite many studies done to predict severe coronavirus 2019 (COVID-19) patients, there is no applicable clinical prediction model to predict and distinguish severe patients early. Based on laboratory and demographic data, we have developed and validated a deep learning model to predict survival and assist in the triage of COVID-19 patients in the early stages. This retrospective study developed a survival prediction model based on the deep learning method using demographic and laboratory data.

Machine learning-based techniques to improve lung transplantation outcomes and complications: a systematic review.

Background: Machine learning has been used to develop predictive models to support clinicians in making better and more reliable decisions. The high volume of collected data in the lung transplant process makes it possible to extract hidden patterns by applying machine learning methods. Our study aims to investigate the application of machine learning methods in lung transplantation.

Rapid implementation of telepharmacy service to improve patient-centric care and multidisciplinary collaboration across hospitals in a COVID era: A cross-sectional qualitative study.

Background And Aim: The COVID-19 pandemic forced healthcare systems to apply new technology-based solutions. The main objective of our study was to describe the conceptual model for rapid implementation of telepharmacy service and the main steps that should be considered.

Method: In response to a limited number of on-site clinical pharmacy specialists and a lack of technology infrastructure, a cross-sectional telepharmacy program was established to support major teaching hospitals.

Medical Informaticians' Skills and Competencies to Achieve Roles and Opportunities: A Qualitative Study.

For Medical Informatics graduates, there is no compatibility between the training knowledge and skills at universities and the job requirements. This study aimed to determine the skills and competencies requirements for medical informatics graduates and possible job positions in an emerging discipline. This qualitative study was conducted using a questionnaire developed by the researchers.

Telemedicine in lung transplant to improve patient-centered care: A systematic review.

Objectives: Long-term care combined with complex follow-up processes is among the essential needs of lung transplantation. Therefore, Telemedicine-based strategies can provide an effective approach for both patients and clinicians by applying remote patient monitoring. Hence, the main objective of this study was to investigate Telemedicine and telehealth usage in lung transplantation.

An evaluation of the quality of COVID-19 websites in terms of HON principles and using DISCERN tool.

Background: As many people relied on information from the Internet for official scientific or academically affiliated information during the COVID-19 pandemic, the quality of information on those websites should be good.

Objective: The main purpose of this study was to evaluate a selection of COVID-19-related websites for the quality of health information provided.

Method: Using Google and Yahoo, 36 English language websites were selected, in accordance with the inclusion criteria.

Pragmatic solutions to enhance self-management skills in solid organ transplant patients: systematic review and thematic analysis.

Background: In organ transplantation, all patients must follow a complex treatment regimen for the rest of their lives. Hence, patients play an active role in the continuity of the care process in the form of self-management tasks. Thus, the main objective of our study was to investigate the pragmatic solutions applied by different studies to enhance adherence to self-management behaviors.

Persian mobile health applications for COVID-19: A use case-based study.

Background: Since the beginning of the COVID-19 outbreak, a significant number of mobile health apps have been created around the world and in Iran to help consequence reduction of this emerging pandemic.

Objectives: This study aimed to review the characteristics of Persian Android and iOS apps related to COVID-19 and determine their use-cases based on a reference model.

Methods: This was a cross-sectional descriptive study conducted in three main steps.

An information-based framework for development national twin registry: Scoping review and focus group discussion.

Background: Registries in various clinical domains have been established in the last decades. The specific genetic structure of twins has enabled researchers to find answers to the role of genetics and the environment in medical sciences. Thus, twin registries were developed across the world to support twin studies.

Determining chronic pain data elements as a first step towards improving quality of care and research in chronic pain.

Background: Chronic pain is a significant clinical problem in the world.  There is still no quite effective treatment for this pain due to its complex nature. Timely retrieval of accurate and comprehensive information through organized clinical and epidemiological studies is an essential prerequisite for providing high quality clinical care and more accurate health planning.

Applied techniques for putting pre-visit planning in clinical practice to empower patient-centered care in the pandemic era: a systematic review and framework suggestion.

Background: One of the main elements of patient-centered care is an enhancement of patient preparedness. Thus, pre-visit planning assessment tools was emerged to prepare and involve patients in their treatment process.

Objective: The main objective of this article was to review the applied tools and techniques for consideration of putting pre-visit planning into practice.

Using data mining techniques to fight and control epidemics: A scoping review.

The main objective of this survey is to study the published articles to determine the most favorite data mining methods and gap of knowledge Since the threat of pandemics has raised concerns for public health, data mining techniques were applied by researchers to reveal the hidden knowledge. Web of Science, Scopus, and PubMed databases were selected for systematic searches. Then, all of the retrieved articles were screened in the stepwise process according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist to select appropriate articles.

Digital Health Solutions to Control the COVID-19 Pandemic in Countries With High Disease Prevalence: Literature Review.

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.

Suggesting a framework for preparedness against the pandemic outbreak based on medical informatics solutions: a thematic analysis.

Background: When an outbreak emerged, each country needs a coherent and preventive plan to deal with epidemics. In the era of technology, adopting informatics-based solutions is essential. The main objective of this study is to propose a conceptual framework to provide a rapid and responsive surveillance system against pandemics.

Enhanced childhood diseases treatment using computational models: Systematic review of intelligent experiments heading to precision medicine.

Introduction: Precision or personalized Medicine (PM) is used for the prevention and treatment of diseases by considering a huge amount of information about individuals variables. Due to high volume of information, AI-based computational models are required. A large set of studies conducted to examine the PM approach to improve childhood clinical outcomes.

The application of wearable smart sensors for monitoring the vital signs of patients in epidemics: a systematic literature review.

Wearable smart sensors are emerging technology for daily monitoring of vital signs with the reducing discomfort and interference with normal human activities. The main objective of this study was to review the applied wearable smart sensors for disease control and vital signs monitoring in epidemics outbreaks. A comprehensive search was conducted in Web of Science, Scopus, IEEE Library, PubMed and Google Scholar databases to identify relevant studies published until June 2, 2020.