فهرست مطالب مجید جنگی

Augmented reality (AR) is one of the new technologies that is used in education, especially medical education. This study aims to determine the requirements for developing an educational application based on AR for teaching clinical coding.

In this descriptive-comparative study conducted in 2022, we first investigated the user interface (UI) and functionality of the AR-based educational applications. The UI features were extracted from 12 similar applications in Persian and English available in Google Play and Cafe Bazaar. To determine the functionality features, the opinions of a panel of experts including professors of clinical coding from Isfahan University of Medical Sciences in Iran were used. 

The UI features included search (found in 3 applications), scanners (found in 11 applications), educational content classification (found in 9 applications), audio/text guides (found in 9 applications), and about us (found in 8 applications) sections. The functionality features included testing of knowledge and using images (2D, 3D).

Due to the theoretical and practical nature of the clinical coding course, a section to solve clinical coding scenarios is an important feature of AR-based educational applications for clinical coding. Also, the use of images (2D, 3D) in these applications can create a deeper impact on students’ learning.

Infectious diseases in the pandemic stage have significant life-threatening, psychological and social effects. Identifying the characteristics associated with peoplechr('39')s cooperation in self-care leads to greater immunity for themselves and others. Therefore, this study was conducted to predict the self-care of the Iranian people according to their individual and social characteristics in face of the Covid-19 pandemic.

A survey study was conducted on 1056 adults aged 18 and over in different provinces of Iran through a form of answering online researcher-made questions (n=40, α=0.9) in social networks in four days. This paper studies the level of self-care of people against Covid 19 pandemic which was conducted with the support of Isfahan University of Medical Sciences in April 2016. Data were analyzed using Student t-test and variance. Moreover, "decision tree technique" was used to identify communication patterns.

The findings showed that the average self-care score in women, the most educated, married women, women aged 41 to 55, housewives and some other occupations was very high. However, the average self-care score of single men with a diploma was average. In general, the mean score of womenchr('39')s self-care was higher than men (P<0.0001) and the educated were more than the less educated literate (P=0.007). There was no significant difference between the self-care scores of the respondents in terms of their marital status and employment.

The results showed that the average scores of self-care in women, more educated people, married women, women in the age group of 41 to 55 years, housewives and some other occupations were reported to be very high; While the average self-care score reported in single men with a diploma was average. Overall, the mean score of self-care reported in women was higher than men (P<0.0001) and people with doctoral education reported more self-care than illiterate people (P=0.007). Besides, there was no significant difference between the self-care scores of the respondents in terms of their marital status (single and married) and their employment status (employed and non-employed).

The recent Coronavirus (SARS-CoV-2) has resulted in a sudden outbreak which has significantly affected various aspects of daily lives. This study was carried out to determine self-care barriers in prevention of Covid-19 according to healthcare experts and laypersons.

A qualitative-quantitative based cross-sectional research was designed. To perform the qualitative phase, group discussion with faculty members and managers in Isfahan University of Medical Sciences and phone interviews with laypersons were carried out. Then, data extracted in this phase were used to design a 40-item questionnaire which was found to be reliable (Cronbach’s Alpha: 0.90), to be completed by Iranian citizens in four days via social networks. In this survey, 1056 people participated. Data analysis was done in SPSS V21.

Self-care barriers according to the qualitative phase of the study included social barriers, psychological barriers, religious barriers, political and management barriers, healthcare system barriers, and information barriers. Political and management barriers (mean score=78.87) and psychological barriers (belief, behavior, personality) (mean score=70.01) were found to be the major self-care barriers. The mean self-care score was 8.5 (in a scale of 0 to 10). The mean self-care scores were significantly higher in women (P<0.0001) and in people with higher levels of education (P=0.007). No significant difference was observed in mean self-care score based on marital status (P=0.61) and occupation (P=0.052).

Health care managers and policymakers could guide people towards more efficient self-care by planning to reduce and overcome barriers identified in this study.

Pathology reports generally use an unstructured text format and contain a complex web of ýrelations between medical concepts. In order to enable computers to understand and analyze ýthe reports’ free text, we aimed to convert these concepts and their relations into a structured ýformat.ý
The training, validation, and evaluation of this implementation study was based on a corpus ýof 258 pathology reports with a positive diagnosis of celiac disease randomly selected from ýamong the records of 2 pathology laboratories. Our proposed system consisted of 3 phases of ýstandardization of celiac disease pathology reports using Delphi technique with 3 experts, ýinformation extraction from free text reports with text mining techniques using Stanford ýParser, and automatic classification of celiac disease stages in marsh system using decision ýtree classifier J48 algorithm.ý
We were successful in extracting information from free text pathology reports and assigning ýeach piece of information to the associated pre-defined fields in standardized template form ýwith an accuracy of 76%. After determining marsh stage for each report in the third phase, ýour system showed an average overall accuracy of 62%. Evaluation of the third phase as an ýindependent system with manually corrected, gold-standard input achieved an accuracy of ýgreater than 84%.ý
The benefits of standardized synoptic pathology reporting include enhanced completeness ýand improved consistency, avoidance of confusion and error, and facilitation of the faster and ýsafer transmission of critical pathological data in comparison with narrative reports.ý

Medical records are considered as an essential element of patient’s health care provision. Due to a rising service provision by healthcare centers, there is an increase in the medical record loads as well. It has led to a series of problems, such as limited physical space, records wearing and an increased need for resources. Moreover, the most important efficiency of records, which is their application in clinical research, is questioned. In the present study, researchers have presented a model of minimum data sets which helps to index and electronically archive hard-copy records according to the selected data and metadata. This study was an applied research type, conducted in three stages in 2013 via modified Delphi technique. Target population consisted of specialists working in hospitals. As the sample, 8 physicians who were specialists or subspecialists participated in interviews and filled out checklist surveys. The collected data were later analyzed using Excel 2013. The results show that data elements such as “final diagnosis” and “operations and others” were the most common items considered by the physicians in clinical follow up, and most common medical records was “operation’s repots”. Finding significant correlation among physician’s research questions was not possible due to large variety of subjects. The researchers presented a framework of minimum data sets for a purposive archiving of records for clinical and research-based applications. This framework can act as the applied goal setting of the retrieval model based on physicians’ clinical requirements in their medical follow-ups. Furthermore, considering physicians’ needs for accessing records through analyzing their probable requests can provide a possibility of data retrieval in diverse conditions.