Fatemeh Bahador, Azam Sabahi, Samaneh Jalali, Fatemeh Ameri,
Volume 16, Issue 6 (Feb 2023)
Abstract
Background and Aim: Diabetes is one of the most common metabolic diseases in Iran and the fifth leading cause of death all over the world. Its spread around the world has created new methods in biomedical research, including artificial intelligence. The present study was carried out to review the studies conducted in the area of artificial intelligence and diabetes in Iran.
Materials and Methods: This study was carried out using a systematic review method. Valid domestic databases, including Irandoc, Magiran, Sid and Google Scholar search engine, were reviewed using the keywords of artificial intelligence and diabetes in Persian both individually and in a combined manner without time limitation until June 20, 2021. A total number of 7495 articles were retrieved, which were screened in different stages (exclusion of duplicates (1824), title and summary of the articles (5884) and full text (30) and finally 20 articles that met the criteria desired by the researchers were carefully reviewed.
Results: Among the retrieved articles, 20 articles met the inclusion criteria, of which 16 articles dealt with methods based on artificial intelligence and 4 articles dealt with the design of new systems based on artificial intelligence. Also, 10 articles examined the role of artificial intelligence in prediction, 8 articles in diagnosis, and 2 articles dealt with the control and management of diabetes. Most of the articles were related to the use of data mining methods such as artificial neural network, decision tree, etc. (16 articles). Some studies also evaluated and compared artificial intelligence methods on application, accuracy and the sensitivity of artificial intelligence in diagnosing and predicting diabetes (10 studies).
Conclusion: A systematic review of articles revealed that the use of data mining methods for diabetes management in Iran has been associated with good progress, but there is a need to design artificial intelligence systems and algorithms and more measures should be taken in the area of diabetes control and management.
Zohreh Javanmard, Marziyhe Meraji, Mahsa Gholizad, Fatemeh Ameri,
Volume 17, Issue 4 (10-2023)
Abstract
Background and Aim: With the increase of the covid-19 epidemic, wearable devices have received a lot of attention in the field of managing this disease. The present systematic review study was conducted with the aim of investigating the role of wearable devices in the management of the covid-19 disease.
Materials and Methods: The present study was conducted according to the guidelines of PRISMA. For this purpose, Web of Science, PubMed, and Scopus databases were searched to retrieve English articles without time limit, until August 16, 2022. The search strategy included the terms “Wearable Device” and “COVID-19”. The inclusion criteria for the study were original and English-language articles that have been carried out to design and implement wearable tools in managing Covid-19. All short articles, letters to the editor, conference abstracts, observational studies, review articles, as well as articles whose full version was not available and in a language other than English, as well as unimplemented items, were excluded from the study process. In order to evaluate the quality of articles, the AXIS evaluation tool was used to evaluate the quality of cross-sectional studies. After selecting the studies, data was collected based on the data extraction form. Then the data was analyzed through the content analysis method.
Results: Finally, 10 articles were included in the present review and the wearable devices introduced in them were examined. Seventy percent of wearable devices are used for symptom monitoring, health status, and quarantine, and 30% for diagnosis. The primary users of these tools were patients, the general public, doctors, and Authorities of statistics and information. The types of wearable devices used were bracelets and smart watches (60%), sensors (30%), pulse oximeters, and chest patches (10%).The most important capability and feature of wearable devices include transferring data and activities to mobile phones and low energy consumption. Using the AXIS quality assessment tool, four studies were rated as very good, five as good, and one as poor.
Conclusion: The review of studies showed that wearable devices provide many capabilities for disease monitoring and patient empowerment, disease diagnosis, and remote monitoring of vital signs of Covid-19 patients. These tools are presented in different forms. It is suggested to develop new tools with the aim of monitoring the covid-19 disease with an emphasis on the use of patients in the form of bracelets and smartwatches, and also the necessary attention should be paid to privacy and confidentiality issues.
