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.

Prediction of ovarian cancer using artificial intelligence tools.

Purpose: Ovarian cancer is a common type of cancer and a leading cause of death in women. Therefore, accurate and fast prediction of ovarian tumors is crucial. One of the appropriate and precise methods for predicting and diagnosing this cancer is to build a model based on artificial intelligence methods.

Evaluating the efficiency of ELISA, monoplex and multiplex probe-based real-time reverse-transcription PCR assays in the detection of SARS-CoV-2 (COVID-19) and influenza A and B viruses: A cross-sectional study.

Background And Aims: The current study aimed to evaluate the efficiency of Enzyme-linked immunosorbent assay (ELISA) assay and monoplex and multiplex real-time reverse-transcription PCR (rRT-PCR) in the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A and B viruses (Flu A and Flu B).

Methods: The SARS-CoV-2 -specific IgG and IgM antibodies, as well as, Flu A (H1N1 and H3N2 serotypes) and Flu B virus antibodies were determined by ELISA assay. The one-step qRT-PCR method was used to detect the SARS-CoV-2 in nasopharyngeal swab samples.

A mobile application for postoperative education of caregivers of children with congenital hypospadias: Requirement analysis.

Background And Aims: Hypospadias, a congenital anomaly, can have long-term effects on sexual, urinary, and reproductive functions, making proper postoperative care essential for desirable outcomes, which could be facilitated through a mobile application for diseases with long-term complications. The aim of this study was to investigate the data and functional requirements or minimum data set of a postoperative education mobile application for caregivers of children with hypospadias.

Methods: A literature review of papers published until April 2023 using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was conducted to determine the data and functional requirements of a mobile application that provides postoperative education to caregivers of children with congenital hypospadias.

Short-term effect of dressing with Dermaheal ointment in the treatment of diabetic foot ulcer: A double-blinded randomized controlled clinical trial.

Background And Aims: Diabetic foot ulcers, a major cause of amputations in diabetics, could benefit from natural products as adjuncts to standard care, given the costs and adverse effects of typical therapies. This study aims to evaluate the short-term effects of dressing with Dermaheal ointment in the treatment of DFUs through a double-blinded randomized controlled clinical trial.

Methods: This double-blinded, placebo-controlled trial included 50 patients with Wagner's ulcer grade I or II, randomly assigned to Dermaheal and placebo groups (received standard treatment and placebo ointment).

Investigating the advantages and disadvantages of electronic logbooks for education goals promotion in medical sciences students: A systematic review.

Background And Aims: Electronic logbook (E-Logbook) is one of the practical software in medical science that serves as an auxiliary tool for comprehensive education, formative evaluation, and student learning documentation in clinical education. E-logbooks are available to people on the Internet without any time or place restrictions. Experts' familiarity with e-logbooks and their advantages and disadvantages can be effective in their better design so professors and students can use their potential benefits.

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.

Discovering associations between radiological features and COVID-19 patients' deterioration.

Background And Aims: Data mining methods are effective and well-known tools for developing predictive models and extracting useful information from various data of patients. The present study aimed to predict the severity of patients with COVID-19 by applying the rule mining method using characteristics of medical images.

Methods: This retrospective study has analyzed the radiological data from 104 COVID-19 hospitalized patients diagnosed with COVID-19 in a hospital in Iran.

Investigating the performance of machine learning algorithms in predicting the survival of COVID-19 patients: A cross section study of Iran.

Background And Aims: Like early diagnosis, predicting the survival of patients with Coronavirus Disease 2019 (COVID-19) is of great importance. Survival prediction models help doctors be more cautious to treat the patients who are at high risk of dying because of medical conditions. This study aims to predict the survival of hospitalized patients with COVID-19 by comparing the accuracy of machine learning (ML) models.

Prognosis of COVID-19 patients using lab tests: A data mining approach.

Background: The rapid prevalence of coronavirus disease 2019 (COVID-19) has caused a pandemic worldwide and affected the lives of millions. The potential fatality of the disease has led to global public health concerns. Apart from clinical practice, artificial intelligence (AI) has provided a new model for the early diagnosis and prediction of disease based on machine learning (ML) algorithms.

Internet of Things and healthcare system: A systematic review of ethical issues.

Background And Aims: The Internet of Things (IoTs) is a set of connected objects and devices that share data and pursue a common goal in different areas. IoT technology can significantly help the healthcare system by enabling the monitoring of elderly and chronic disease patients. Along with the growth of this technology, its challenges and limitations such as Connectivity, Compatibility, Standards, cost, legal, and ethical also increase.

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.

The trend of top five types of poisonings in hospitalized patients based on ICD-10 in the northeast of Iran during 2012-2018: A cross-sectional study.

Background And Aims: Poisoning remains a major health issue in developing countries with high morbidity and mortality rates; also it is one of the most common causes of admission to hospitals. This study aimed to investigate the trend of the top five types of poisonings in hospitalized patients according to the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) in Imam Reza hospital, Mashhad, Iran.

Methods: This was a cross-sectional study performed from March 20, 2012, until September 22, 2018.