Social network analysis of Iranian researchers on medical parasitology: A 41 year co-authorship survey

Background: The aim of this study was to survey the Iranian Parasitology researchers� performance, and analyse and visualize the scientific outputs of their co-authorship network. Methods: This study was conducted using scientometric method and social network analysis (SNA). The data extracted from the Web of Science (WoS) databases in July 10th 2014. Totally, 1048documents of all types in research area of Parasitology during 1972-2013 by Iranian researches retrieved. The coauthorship map was drawn utilizing NETDRAW, Coauthor.exe, and UCINET softwares and was analysed based on SNA measures. Results: The researchers� co-authorship network consisted of 78 authors and its density degree is 0.57. �Mohebali� ranked top in all of centrality measures.The most of the publications were related to 2012, �Mohebali� with about 9 of all documents was the Iranian most prolific author in Parasitology field. The Iranian researches have published mostly (266 documents) in �Iranian Journal of Parasitology�, and the most of the documents belong to �Tropical Medicine� subject field. The most of Iranian researchers� scientific cooperation was performed with England and United States. Conclusion: Bringing forth density degree (is 0.57) showed that this network has an almost medium density. Indeed, the authors have had relations in moderate level with each other in the network. The findings of this study can be identified aspects of scientific collaboration, and help policy makers of Parasitology field research. © 2016, Tehran University of Medical Sciences (TUMS). All rights reserved

Evaluation of Iranian Scientists Productions in Biotechnology and Applied Microbiology based on ISI through 2000 to 2008

In most countries, internationally indexed scientific publications provide the possibility for the scientometric experts to study their scientific progress. In Iran, the number of scientific productions indexed in ISI was 323 in 1993 and rose to 14832 in 2008 showing about 46 manifolds. The main aim of this research is to illustrate the dynamic structure of scientific productions of Iranian biotechnologists and applied microbiologists in WOS database during 2000–2008. The data was gathered through searching WOS database of ISI. The field of search was country (CU=IRAN). 681 scientific products were reported to be indexed in ISI. Iranians' international collaboration has been mainly with Canadian, Swedish and Australian coauthors. Compared to other Iranian universities, University of Tehran, Tarbiat Modares University and Tehran University of Medical Sciences have contributed mostly to ISI. Iranian biotechnologists’ and microbiologists’ intercontinental collaboration is generally in Biochemistry and Molecular Biology, Engineering and chemical and Biochemical research. There has been an increase in the fundamental research activities in Biotechnology and Applied Microbiology research projects which have triggered motivation for higher contribution to ISI

Improving the distribution of rural health houses using elicitation and GIS in Khuzestan province (The southwest of Iran)

Background: Rural health houses constitute a major provider of some primary health services in the villages of Iran. Given the challenges of providing health services in rural areas, health houses should be established based on the criteria of health network systems (HNSs). The value of these criteria and their precedence over others have not yet been thoroughly investigated. The present study was conducted to propose a model for improving the distribution of rural health houses in HNSs. Methods: The present applied study was conducted in Khuzestan province in the southwest of Iran in 2014-2016. First, the descriptive and spatial data required were collected and entered into ArcGIS after modifications, and the Geodatabase was then created. Based on the criteria of the HNS and according to experts� opinions, the main criteria and the sub-criteria for an optimal site selection were determined. To determine the criteria�s coefficient of importance (ie, their weight), the main criteria and the sub-criteria were compared in pairs according to experts� opinions. The results of the pairwise comparisons were entered into Expert Choice and the weight of the main criteria and the sub-criteria were determined using the analytic hierarchy process (AHP). The application layers were then formed in geographic information system (GIS). A model was ultimately proposed in the GIS for the optimal distribution of rural health houses by overlaying the weighting layers and the other layers related to villages and rural health houses. Results: Based on the experts� opinions, six criteria were determined as the main criteria for an optimal site selection for rural health houses, including welfare infrastructures, population, dispersion, accessibility, corresponding routes, distance to the rural health center and the absence of natural barriers to accessibility. Of the main criteria proposed, the highest weight was given to �population� (0.506). The priorities suggested in the proposed model for establishing rural health houses are presented within five zoning levels �from excellent to very poor. Conclusion: The results of the study showed that the proposed model can help provide a better picture of the distribution of rural health houses. The GIS is recommended to be used as a means of making the HNS more efficient. © 2018 The Author(s); Published by Kerman University of Medical Sciences

Improving the distribution of rural health houses using elicitation and GIS in Khuzestan province (The southwest of Iran)

Background: Rural health houses constitute a major provider of some primary health services in the villages of Iran. Given the challenges of providing health services in rural areas, health houses should be established based on the criteria of health network systems (HNSs). The value of these criteria and their precedence over others have not yet been thoroughly investigated. The present study was conducted to propose a model for improving the distribution of rural health houses in HNSs. Methods: The present applied study was conducted in Khuzestan province in the southwest of Iran in 2014-2016. First, the descriptive and spatial data required were collected and entered into ArcGIS after modifications, and the Geodatabase was then created. Based on the criteria of the HNS and according to experts� opinions, the main criteria and the sub-criteria for an optimal site selection were determined. To determine the criteria�s coefficient of importance (ie, their weight), the main criteria and the sub-criteria were compared in pairs according to experts� opinions. The results of the pairwise comparisons were entered into Expert Choice and the weight of the main criteria and the sub-criteria were determined using the analytic hierarchy process (AHP). The application layers were then formed in geographic information system (GIS). A model was ultimately proposed in the GIS for the optimal distribution of rural health houses by overlaying the weighting layers and the other layers related to villages and rural health houses. Results: Based on the experts� opinions, six criteria were determined as the main criteria for an optimal site selection for rural health houses, including welfare infrastructures, population, dispersion, accessibility, corresponding routes, distance to the rural health center and the absence of natural barriers to accessibility. Of the main criteria proposed, the highest weight was given to �population� (0.506). The priorities suggested in the proposed model for establishing rural health houses are presented within five zoning levels �from excellent to very poor. Conclusion: The results of the study showed that the proposed model can help provide a better picture of the distribution of rural health houses. The GIS is recommended to be used as a means of making the HNS more efficient. © 2018 The Author(s); Published by Kerman University of Medical Sciences

The relationship between information literacy, internet addiction and general health of an Iranian medical students

Introduction: Given the prevalence of Internet use worldwide and its existing risks to societies especially the youngsters, information literacy can affect the use of Internet. Hence, the objective of present study is to assess the relationship between information literacy and Internet addiction and then to investigate the relationship between Internet addiction and general health of students in Iran University of Medical Sciences. Materials and Methods: It is an analytical cross-sectional study which was conducted during 2016 on students in Iran University of Medical Sciences (Tehran, Iran). The sample size for the surveyed community of 6,500 university students was 362 from the Cochran sample size formula. Then, using a simple random sampling method, from each of the colleges, the sample size was selected according to the student population. Three questionnaires of information literacy, Yang's Internet addiction, and general health scale (GHQ-28) were distributed among students. Finally, 365 questionnaires were collected and analyzed. Results: 29.9 of students were about to be addicted to the Internet, 1.3 had symptoms of Internet addiction and 68.8 had no addiction. In terms of information literacy, most of the students were in moderate level (60.5 moderate, 3.3 low, and 36.2 high information literacy level). There was a significant inverse relationship between increasing of information literacy and the Internet addiction (r = -0.45 and p<0.001). The score of general health demonstrated an inverse and significant relationship in different levels of Internet addiction (P <0.001). Conclusion: According to the findings of this study, it was perceived that the higher the information literacy, the lower the level of Internet addiction; besides, reduction of internet addiction increased the general health of students. Therefore, considering the importance of students as the leading group in societies, and favorable consequences of increased information literacy, universities' authorities have to develop and run specific programs within the educational and research schedule in order to increase the students' information literacy. Accordingly, undesirable outcomes of Internet use would be diminished and general health of society would be improved. © 2018, Semnan University of Medical Sciences. All rights reserved

The relationship between information literacy, internet addiction and general health of an Iranian medical students

Introduction: Given the prevalence of Internet use worldwide and its existing risks to societies especially the youngsters, information literacy can affect the use of Internet. Hence, the objective of present study is to assess the relationship between information literacy and Internet addiction and then to investigate the relationship between Internet addiction and general health of students in Iran University of Medical Sciences. Materials and Methods: It is an analytical cross-sectional study which was conducted during 2016 on students in Iran University of Medical Sciences (Tehran, Iran). The sample size for the surveyed community of 6,500 university students was 362 from the Cochran sample size formula. Then, using a simple random sampling method, from each of the colleges, the sample size was selected according to the student population. Three questionnaires of information literacy, Yang's Internet addiction, and general health scale (GHQ-28) were distributed among students. Finally, 365 questionnaires were collected and analyzed. Results: 29.9 of students were about to be addicted to the Internet, 1.3 had symptoms of Internet addiction and 68.8 had no addiction. In terms of information literacy, most of the students were in moderate level (60.5 moderate, 3.3 low, and 36.2 high information literacy level). There was a significant inverse relationship between increasing of information literacy and the Internet addiction (r = -0.45 and p<0.001). The score of general health demonstrated an inverse and significant relationship in different levels of Internet addiction (P <0.001). Conclusion: According to the findings of this study, it was perceived that the higher the information literacy, the lower the level of Internet addiction; besides, reduction of internet addiction increased the general health of students. Therefore, considering the importance of students as the leading group in societies, and favorable consequences of increased information literacy, universities' authorities have to develop and run specific programs within the educational and research schedule in order to increase the students' information literacy. Accordingly, undesirable outcomes of Internet use would be diminished and general health of society would be improved. © 2018, Semnan University of Medical Sciences. All rights reserved

Diabetes knowledge translation status in developing countries: A mixed method study among diabetes researchers in case of Iran

Background: Despite considerable investment in research, the existing research evidence is frequently not implemented and/or leads to useless or detrimental care in healthcare. The knowledge�practice gap proposed as one of the main causes of not achieving the treatment goals in diabetes. Iran also is facing a difference between the production and utilization of the knowledge of diabetes. The aim of this study was to assess the status of diabetes knowledge translation (KT) in Iran. Methods: This was a survey that executed in 2015 by concurrent mixed methods approach in a descriptive, cross�sectional method. The research population was 65 diabetes researchers from 14 diabetes research centers throughout Iran. The research was carried out via the self�assessment tool for research institutes (SATORI), a valid and reliable tool. Focus group discussions were used to complete this tool. The data were analyzed using quantitative (descriptive method by Excel software) and qualitative approaches (thematic analysis) based on SATORI�extracted seven themes. Results: The mean of scores �the question of research,� �knowledge production,� �knowledge transfer,� �promoting the use of evidence,� and all aspects altogether were 2.48, 2.80, 2.18, 2.06, and 2.39, respectively. The themes �research quality and timeliness� and �promoting and evaluating the use of evidence� received the lowest (1.91) and highest mean scores (2.94), respectively. Except for the theme �interaction with research users� with a relatively mediocre scores (2.63), the other areas had scores below the mean. Conclusions: The overall status of diabetes KT in Iran was lower than the ideal situation. There are many challenges that require great interventions at the organizational or macro level. To reinforce diabetes KT in Iran, it should hold a more leading and centralized function in the strategies of the country�s diabetes research system. © 2016 International Journal of Preventive Medicine

Mapping Scheme of Traditional Iranian Medicine Cluster’s Crotch in the Structure of Metathesaurus of Unified Medical Language System (UMLS)

Background & Aim: Unified Medical Language System (UMLS) is an extensive ontology of biomedical knowledge developed and maintained by U.S. National Library of Medicine (NLM). Traditional Iranian Medicine (TIM) does not have any position in the structure of metathesaurus of UMLS. The main aim of this study was designing a scheme of TIM cluster's crotch mapping in the structure of metathesaurus of UMLS. Moreover, the TIM position and its proportion in the domain of vocabulary and concepts of universal medical knowledge was another aim of this study.Materials and Methods: System analysis was the method of this study. To investigate structure of UMLS metathesaurus, and to survey lacking of TIM cluster's crotch, we applied UMLS Knowledge Source (KS) by using inductive, deductive, inductive-deductive approaches.Results: One Concept Unique Identifier (CUI); two synonym terms with Lexical Unique Identifier (LUI), L0025131 and L6330122; two ancestor and parent concept; nine concepts which with TIM crotch were the child concepts of two ancestor and parent; eighteen sibling concepts; six narrower; and five other related found concepts were identified for the proposal TIM crotch mapping in metathesaurus of UMLS. In addition, we found the "Biomedical Occupation or Discipline" semantic type assigned to it.Conclusions: Current domain of metathesaurus of UMLS does not represent complete and formal domain and position of TIM. Therefore, this metathesaurus needs to depict a domain and position for TIM

Comparison of machine-learning algorithms efficiency to build a predictive model for mortality risk in COVID-19 hospitalized patients

Introduction: The rapid worldwide outbreak of SARS-CoV-2 has posed serious and unprecedented challenges to healthcare systems in predicting disease behavior and outcomes. To overcome these challenges or ambiguities, this study aimed to create and validate several predictive models using of selected ML algorithms to stratify the mortality risk in COVID-19 hospitalized patients and choice the best performing algorithm. Materials and Methods: Data of 1224 hospitalized patients with COVID-19 diagnosis based on the findings of the confirmed-laboratory test were extracted from the Ilam COVID-19 registry (Ilam CoV reg) database. Then the most important clinical parameters in the COVID-19 mortality were identified and used as inputs of the selected ML algorithms, including K-Nearest Network (KNN), Support Vector Machine (SVM), Logistic Regression (LR) and Random Forest (RF). Finally, the performance of the developed models was compared based on different confusion matrix evaluation criteria and the most appropriate predictive model was determined. Results: A total of 17 parameters were identified as the most influential clinical variables in the mortality of COVID-19. By comparing the performance of ML algorithms according to various evaluation criteria, the KNN algorithm with precision of 94.21, accuracy of 93.74, recall of 100, F-measure of 93.2 and ROC of 92.23, yielded better performance than other developed algorithms. Conclusion: KNN enables a reasonable level of accuracy and certainty in predicting the mortality of patients with COVID-19 and potentially facilitates identifing high risk patients and, inform proper interventions by the clinicians. © 2022, Semnan University of Medical Sciences. All rights reserved

Design and implementation of an intelligent clinical decision support system for diagnosis and prediction of chronic kidney disease

Introduction: Chronic kidney disease (CKD) is one of the most important public health concerns worldwide. The steady increase in the number of people with End-stage renal disease (ESRD) needing a kidney transplant to survive and incur high costs, highlights early diagnosis and treatment of the disease. This study aimed to design a Clinical Decision Support System (CDSS) for diagnosing CKD and predicting the advanced stage to achieve better management and treatment of the disease. Materials and Methods: In this retrospective and developmental study, we studied the records of 600 suspected CKD cases with 22 variables referred to ShahidLabbafinejad Hospital in Tehran from 2019 to 2020. Data mining algorithms such as Naïve Bayesian, Random Forest, Multilayer Perceptron neural network, and J-48 decision tree were developed based on extracted variables. Then the recital of selected models was compared by some performance indices and 10-fold cross-validation. Finally, the most appropriate prediction model in terms of performance was implemented using the C # programming language. Results: Random Forest classification algorithm with an accuracy of 99.8 and 88.66, specificity of 100 and 93.8, the sensitivity of 99.75 and 88.7, f-measure of 99.8 and 88.7, kappa score of 99.4 and 82.73, and ROC of 100 and 90.52 was identified as the best data mining model for CKD diagnosis and prediction respectively. Conclusion: The developed MC-DMK system based random Forestcan be used practically in clinical settings. © 2022, Semnan University of Medical Sciences. All rights reserved