A Framework for Neonatal Prematurity Information System Development Based on a Systematic Review on Current Registries: An Original Research.

Background: Registries are regarded as a just valuable fount of data on determining neonates suffering prematurity or low birth weight (LBW), ameliorating provided care, and developing studies.

Objective: This study aimed to probe the studies, including premature infants' registries, adapt the needed minimum data set, and provide an offered framework for premature infants' registries.

Material And Methods: For this descriptive study, electronic databases including PubMed, Scopus, Web of Science, ProQuest, and Embase/Medline were searched.

Designing and Evaluating a Nutrition Recommender System for Improving Food Security in a Developing Country.

Background: Due to the increased price of foods in recent years and the diminished food security in Iran, nutrition recommender systems can suggest the most suitable and affordable foods and diets to users based on their health status and food preferences. The present study aimed to design and evaluate a recommender system to suggest healthy and affordable meals and provide a tele-nutrition consulting service.

Methods: This applied three-phase study was conducted in 2020.

Development and evaluation of a clinical decision support system for early diagnosis of acute appendicitis.

The most frequent reason for individuals experiencing abdominal discomfort to be referred to emergency departments of hospitals is acute appendicitis, and the most frequent emergency surgery performed is an appendectomy. The purpose of this study was to design and develop an intelligent clinical decision support system for the timely and accurate diagnosis of acute appendicitis. The number of participants which is equal to 181 was chosen as the sample size for developing and evaluating neural networks.

Designing and evaluating the children's developmental motor disorders system: an experience from a developing country.

Background: Developmental disorders are a prevalent problem in the health sector of low- and middle-income countries (LMICs), and children in these countries are at greater risk. A registry system is helpful and vital to monitoring and managing this disease.

Objective: The present study aims to develop an electronic registry system for children's developmental motor disorders.

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.

Evaluation of the PSO Metaheuristic Algorithm in Different Types of Sleep Apnea Diagnosis Using RR Intervals.

Background: Sleep apnea is one of the most common sleep disorders that facilitating and accelerating its diagnosis will have positive results on its future trend.

Objective: This study aimed to diagnosis the sleep apnea types using the optimized neural network.

Material And Methods: This descriptive-analytical study was done on 50 cases of patients referred to the sleep clinic of Imam Khomeini Hospital in Tehran, including 11 normal, 13 mild, 17 moderate and 9 severe cases.

Myocardial Infarction Prediction and Estimating the Importance of its Risk Factors Using Prediction Models.

Background: According to World Health Organization (WHO), cardiovascular diseases (CVDs) are the leading cause of death globally. Although significant progress has been made in the diagnosis of CVDs, more investigation can be helpful. Therefore, this study aimed to predict the risk of myocardial infarction (MI) using data mining algorithms.

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.

Design, implementation, and evaluation of an innovative intelligence information management system for premature infants.

Introduction: Low birth weight is the most important condition of neonatal community health and the main cause of neonates' mortality. Identifying the indexes associated with this condition, and factors to prevent, and managing related data can help reduce the birth of premature infants to reduce the mortality rate due to this condition. The goal of present study was to design, implement and evaluate an innovative intelligence information management system for premature infants.

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.

The silent crisis of child abuse in the COVID-19 pandemic: A scoping review.

Background And Aims: The global outbreak of COVID-19 has become an international concern. The lives of children are severely affected by COVID-19 pandemic. There is evidence of a pandemic impact on violence against children.

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.

Global perspective on pediatric growth hormone registries: a systematic review.

Background: Registries are considered valuable data sources for identification of pediatric conditions treated with growth hormone (GH), and their follow-up. Currently, there is no systematic literature review on the scope and characteristics of pediatric GH registries. Therefore, the purpose of this systematic review is to identify worldwide registries reported on pediatric GH treatment and to provide a summary of their main characteristics.

Validity and reliability of the Persian version of the Patient readiness to engage in health information technology (PRE-HIT) instrument.

Background: The Patient readiness to engage in health information technology (PRE-HIT) is a conceptually and psychometrically validated questionnaire survey tool to measure willingness of patients with chronic conditions to use health information technology (HIT) resources.

Objectives: This study aimed to translate and validate a health information technology readiness instrument, the PRE-HIT instrument, into the Persian language.

Methods: A rigorous process was followed to translate the PRE-HIT instrument into the Persian language.

Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects.

Clinical decision support systems (CDSSs) interventions were used to improve the life quality and safety in patients and also to improve practitioner performance, especially in the field of medication. Therefore, the aim of the paper was to summarize the available evidence on the impact, outcomes and significant factors on the implementation of CDSS in the field of medicine. This study is a systematic literature review.

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.

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.

Management of the essential data element in the differential diagnosis of oral medicine: An effective step in promoting oral health.

Background: Oral soft tissue diseases include a broad spectrum, and the wide array of patient data elements need to be processed in their diagnosis. One of the biggest and most basic challenges is the analysis of this huge amount of complex patient data in an increasing number of complicated clinical decisions. This study seeks to identify the necessary steps for collecting and management of these data elements through establishing a consensus-based framework.

Development and validation of the Neonatal Abstinence Syndrome Minimum Data Set (NAS-MDS): a systematic review, focus group discussion, and Delphi technique.

Objectives: Neonatal abstinence syndrome (NAS) is a combination of symptoms in infants exposed to any variety of substances in utero. Information systems and registries help to collect information about these patients; however, there is always a deep gap between complete and accurate information to be collected, understood, and applied in the health care system; thus, defining a minimum data sets (MDS) as one of the primarily steps of designing a registry system is essential. The aim of this study was to develop an MDS of the registry for infants with NAS in Iran.

Design and Psychometrics of the Assessment Instrument for Innovation Capabilities of Medical Sciences Universities Using the Cube Model Approach.

Background: To investigate any subject, a scholar needs a suitable instrument to collect the required information with the utmost accuracy and the least amount of error. Therefore, this study aimed at designing and conducting a psychometric analysis of an assessment instrument for innovation capabilities of Medical Sciences Universities using the Cube Model Approach.

Methods: This study began by searching in questionnaires in the fields of input and process, considering innovation outcomes.

Identification and ranking of important bio-elements in drug-drug interaction by Market Basket Analysis.

Drug-drug interactions (DDIs) are the main causes of the adverse drug reactions and the nature of the functional and molecular complexity of drugs behavior in the human body make DDIs hard to prevent and threat. With the aid of new technologies derived from mathematical and computational science, the DDI problems can be addressed with a minimum cost and effort. The Market Basket Analysis (MBA) is known as a powerful method for the identification of co-occurrence of matters for the discovery of patterns and the frequency of the elements involved.

Identification and Validation of Requirements for a Registry System of Children's Developmental Motor Disorders in Iran.

Background:  Despite recent advances in the field of medical sciences, children's developmental motor disorders (DMDs) are considered as one of the challenges in this area. Establishment of electronic systems for recording and monitoring children's DMDs can play an effective role in identifying patients and reducing the costs and consequences of the disease management. The aim of this study was to identify and validate the requirements for a registry system of children's DMDs in Iran.