Hospital real-time location system (A practical approach in healthcare): A narrative review article

The Hospital Real-time Location Systems (HRTLS), deal with monitoring the patients, medical staff and valuable medical equipment in emergency situations. Therefore, the study aimed to propose Hospital Real-Time Location Systems based on the novel technologies in Iran. Methods: In this narrative-review, the articles and official reports on HRTLS, were gathered and analyzed from related textbooks and indexing sites with the defined keywords in English or Persian. The search of databases such as IDTechEx, IEEE, PubMed Central, Science Direct, EMBASE/Excerpta Medica, Scopus, Web of Science, Elsevier journals, WHO publications and Google Scholar was performed to reconfirm the efficiency of HRTLS from 2006 to 2017. Results: Various technologies have been used in the current systems, which have led to the reduced error rate, costs and increased speed of providing the healthcare services. Applications of these systems include tracking of patient�s, medical staff and valuable medical assets. Besides, achieving the patient & staff satisfaction is among other basic applications of these Systems. The accurate data exchange and processes control are considered as positive aspects of this technology. Conclusion: HRTLS has great importance in healthcare systems and its efficiency in medical centers is reliable; hence, it seems necessary to determine the organization�s requirements, apply novel technologies such as cloud computing and Internet of things, and integrate them to get access to maximum advantages in Iranian healthcare centers. © 2019, Iranian Journal of Public Health. All rights reserved

Predicting coronary artery disease: A comparison between two data mining algorithms

Background: Cardiovascular diseases (CADs) are the first leading cause of death across the world. World Health Organization has estimated that morality rate caused by heart diseases will mount to 23 million cases by 2030. Hence, the use of data mining algorithms could be useful in predicting coronary artery diseases. Therefore, the present study aimed to compare the positive predictive value (PPV) of CAD using artificial neural network (ANN) and SVM algorithms and their distinction in terms of predicting CAD in the selected hospitals. Methods: The present study was conducted by using data mining techniques. The research sample was the medical records of the patients with coronary artery disease who were hospitalized in three hospitals affiliated to AJA University of Medical Sciences between March 2016 and March 2017 (n = 1324). The dataset and the predicting variables used in this study was the same for both data mining techniques. Totally, 25 variables affecting CAD were selected and related data were extracted. After normalizing and cleaning the data, they were entered into SPSS (V23.0) and Excel 2013. Then, R 3.3.2 was used for statistical computing. Results: The SVM model had lower MAPE (112.03), higher Hosmer-Lemeshow test's result (16.71), and higher sensitivity (92.23). Moreover, variables affecting CAD (74.42) yielded better goodness of fit in SVM model and provided more accurate result than the ANN model. On the other hand, since the area under the receiver operating characteristic (ROC) curve in the SVM algorithm was more than this area in ANN model, it could be concluded that SVM model had higher accuracy than the ANN model. Conclusion: According to the results, the SVM algorithm presented higher accuracy and better performance than the ANN model and was characterized with higher power and sensitivity. Overall, it provided a better classification for the prediction of CAD. The use of other data mining algorithms are suggested to improve the positive predictive value of the disease prediction. © 2019 The Author(s)

Hospital real-time location system (A practical approach in healthcare): A narrative review article

The Hospital Real-time Location Systems (HRTLS), deal with monitoring the patients, medical staff and valuable medical equipment in emergency situations. Therefore, the study aimed to propose Hospital Real-Time Location Systems based on the novel technologies in Iran. Methods: In this narrative-review, the articles and official reports on HRTLS, were gathered and analyzed from related textbooks and indexing sites with the defined keywords in English or Persian. The search of databases such as IDTechEx, IEEE, PubMed Central, Science Direct, EMBASE/Excerpta Medica, Scopus, Web of Science, Elsevier journals, WHO publications and Google Scholar was performed to reconfirm the efficiency of HRTLS from 2006 to 2017. Results: Various technologies have been used in the current systems, which have led to the reduced error rate, costs and increased speed of providing the healthcare services. Applications of these systems include tracking of patient�s, medical staff and valuable medical assets. Besides, achieving the patient & staff satisfaction is among other basic applications of these Systems. The accurate data exchange and processes control are considered as positive aspects of this technology. Conclusion: HRTLS has great importance in healthcare systems and its efficiency in medical centers is reliable; hence, it seems necessary to determine the organization�s requirements, apply novel technologies such as cloud computing and Internet of things, and integrate them to get access to maximum advantages in Iranian healthcare centers. © 2019, Iranian Journal of Public Health. All rights reserved

Diversity, mitochondrial phylogeny, and ichthyogeography of the Capoeta capoeta complex (Teleostei: Cyprinidae)

Fish species of the genus Capoeta are known for their special mouth morphology (inferior mouth with the horny edge to the lower jaw), short dorsal fin with seven to nine branched rays, and their tumultuous taxonomic history. The genus Capoeta has had a complex evolutionary history with high diversification in the Middle East and is closely related with genus Luciobarbus. Earlier attempts to clarify the complex taxonomy of the group established four species groups, namely C. capoeta, C. damascina, C. tinca, and C. trutta species group. Based on this study, the C. capoeta group currently includes nine taxa (seven previous + two newly included members) and all reviewed in this paper based on morphological characters and mitochondrial genes. Capoeta macrolepis, revalidated as a distinct species, and Capoeta fusca are additional members of the C. capoeta group. Molecular time tree shows that the separation of Capoeta from its relative Luciobarbus was about 12.43-16.99 MYA. Based on the time tree presented herein, the high diversity of Capoeta in the Tigris-Euphrates system, the nesting of Capoeta within the tetraploid Luciobarbus in the mitochondrial trees and the high diversity of Luciobarbus in the Tigris-Euphrates system, it is proposed that the origination and diversification of Capoeta occurred in the palaeo-drainages of the Tigris-Euphrates system. From here, dispersion of Capoeta to the other nearby basins could have been possible through freshwater corridors during the Pliocene or Pleistocene