Which criteria are important in usability evaluation of mHealth applications: an umbrella review.

Introduction: Usability plays a critical role in the design of mHealth applications. A well-designed app enhances user experience and contributes to better healthcare outcomes. However, it remains unclear which usability criteria are often neglected, leading to issues in the actual use of these applications.

AFEX-Net: Adaptive feature extraction convolutional neural network for classifying computerized tomography images.

Purpose: Deep convolutional neural networks are favored methods that are widely used in medical image processing due to their demonstrated performance in this area. Recently, the emergence of new lung diseases, such as COVID-19, and the possibility of early detection of their symptoms from chest computerized tomography images has attracted many researchers to classify diseases by training deep convolutional neural networks on lung computerized tomography images. The trained networks are expected to distinguish between different lung indications in various diseases, especially at the early stages.

The viewpoints of parents of children with mental disorders regarding the confidentiality and security of their children's information in the Iranian national electronic health record system.

Introduction: Electronic health records help collect and communicate patient information among healthcare providers. The confidentiality of information, especially for patients with mental disorders, is paramount due to its profound impacts on individuals' lives' social and personal aspects. This study aimed to investigate the viewpoints and concerns of parents of children with mental disorders regarding the confidentiality and security of their children's information in the Iranian National Electronic Health Record System (IEHRS).

A systematic review of data elements of computerized physician order entry (CPOE): mapping the data to FHIR.

Objective: Medication errors are the third leading cause of death. There are several methods to prevent prescription errors, one of which is to use a Computerized Physician Order Entry system (CPOE). In a CPOE system, necessary data needs to be collected so that making decisions about prescribing medications and treatment plans could be made.

The relationship between e-health literacy and information technology acceptance, and the willingness to share personal and health information among pregnant women.

Background: Many factors may affect pregnant women's willingness to accept information (IT) technology and share their personal and health information. One of these factors is their e-health literacy level.

Objective: To investigate the relationship between e-health literacy and IT acceptance, as well as the willingness of pregnant women to share their information.

Prediction of mortality risk and duration of hospitalization of COVID-19 patients with chronic comorbidities based on machine learning algorithms.

Background: The severity of coronavirus (COVID-19) in patients with chronic comorbidities is much higher than in other patients, which can lead to their death. Machine learning (ML) algorithms as a potential solution for rapid and early clinical evaluation of the severity of the disease can help in allocating and prioritizing resources to reduce mortality.

Objective: The objective of this study was to predict the mortality risk and length of stay (LoS) of patients with COVID-19 and history of chronic comorbidities using ML algorithms.

The role of mobile health in prevention, diagnosis, treatment and self-care of COVID-19 from the healthcare professionals' perspectives.

Background: To facilitate disease management, understanding the attitude of healthcare professionals regarding the use of this tool can help mobile health (mHealth) program developers develop appropriate interventions.

Aims: To assess the perspective of healthcare professionals regarding the contribution of mobile-based interventions in the prevention, diagnosis, self-care, and treatment (PDST) of COVID-19.

Methods: This is a survey study conducted in 2020 in Iran with 81 questions.

Developing a minimum data set for cardiovascular Computerized Physician Order Entry (CPOE) and mapping the data set to FHIR: A multi-method approach.

Many medical errors occur in the process of treating cardiovascular patients, and most of these errors are related to prescription errors. There are several, one of the methods to prevent prescription errors is the use of a computerized physician order entry (CPOE) system. One of the obstacles of implementing this system is improper design and non-compliance with user needs.

A Rule Based Intelligent Software to Predict Length of Stay and the Mortality Rate in Trauma Patients in the Intensive Care Unit.

Background: Intensive Care Unit (ICU) has the highest mortality rate in the world. ICU has special equipment that leads to the hospital's most costly parts. The length of stay in the ICU is a special issue, and reducing this time is a practical approach.

Barriers and challenges of using health information technology in home care: A systematic review.

Objective: Despite the benefits of applying Information technology (IT) in-home care some challenges may affect the quality of the services. To deal with these challenges, it is required to identify them before providing such services. Therefore, the aim of this study is to systematically determine the challenges and barriers of using health IT in-home care.

Machine Learning Models for Image-Based Diagnosis and Prognosis of COVID-19: Systematic Review.

Background: Accurate and timely diagnosis and effective prognosis of the disease is important to provide the best possible care for patients with COVID-19 and reduce the burden on the health care system. Machine learning methods can play a vital role in the diagnosis of COVID-19 by processing chest x-ray images.

Objective: The aim of this study is to summarize information on the use of intelligent models for the diagnosis and prognosis of COVID-19 to help with early and timely diagnosis, minimize prolonged diagnosis, and improve overall health care.

Evaluating hospital information system according to ISO 9241 part 12.

Objectives: Compliance with standards in designing information systems leads to better utilization and ease of use for users. In this study, the compliance of a widely used hospital information system (HIS) with ISO 9241 part 12 was assessed.

Methods: This applied research is a descriptive, cross-sectional study in which the HIS of 8 hospitals affiliated with Kerman University of Medical Sciences was evaluated based on ISO 9241 part 12.

Spatio-temporal mapping of breast and prostate cancers in South Iran from 2014 to 2017.

Background: The most common gender-specific malignancies are cancers of the breast and the prostate. In developing countries, cancer screening of all at risk is impractical because of healthcare resource limitations. Thus, determining high-risk areas might be an important first screening step.

Machine learning models in breast cancer survival prediction.

Background: Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer.