Although Iran has a deep history in herbal medicine and great heritage of ancient medical scholars, few efforts have been made to evaluate ethnopharmacological aspects of medicinal plants in this country. In the present study, the authors have reviewed all important literature about the ethnopharmacological investigations on medicinal plants used in the last decade in Iran. All provinces of Iran were categorized according to a phytogeographical division. Information was collected through bibliographic investigations from scientific journals and books. Afterward, the data were analyzed through the construction of specific ecological regions of the country. Fifty-five references reporting medicinal plants in five ecological zones were retrieved. The Irano-Turanian subregion has produced the greatest number of publications in this field among others (47%). Results illustrate that the most reported botanical families were Lamiaceae and Asteraceae (28.57% and 27.73%, respectively). Among various illnesses reported for these plants, gastrointestinal (30.15%), respiratory problems (14.28%), diabetes (11.11%), and cold/flu (11.11%) were the most cited. The most frequently cited medicinal uses were attributed to decoction and infusion preparations. Iran has a rich history of knowledge about phytotherapy and has also a diverse geographical regions, and a plant flora that is a good candidate for drug discovery. Documentation of indigenous knowledge about herbal medicine used by Iranian tribes is vital for the future development of herbal drugs. Ethnopharmacological studies of Iranian folk medicine with quantitative analytical techniques are warranted to find drug candidates, and also to preserve the precious knowledge of the Iranian folk medicine.

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Introduction: Hypotension during Hemodialysis often increases mortality in patients undergoing dialysis for a long time. Hypotension is the most frequent adverse event during hemodialysis; therefore, the present study was conducted to investigate hypotension value of patients and present a predictive model using descriptive data mining. Methods: In this cross-sectional study, conducted from May-June 2016, the data were extracted from Ali Ibn Abi Talib hospital in Zahedan and were then analyzed using Clementine 12.0. The model was presented using K-Means, C5.0 and CART algorithms. Results: According to the findings the parameters influencing hypotension were buffer type and blood flow the importance of which was verified through clustering and the extracted rules from the model. Discussion: The use of new modelling methods to analyze dialysis data and discover the existing relationships among them, changes the attitudes of dialysis personnel towards the process of dialysis and dialysis care. The evaluation of hypotension in hemodialysis patients helps a faster and more precise identification of hypotension. It would also facilitate proper and preventive management which enhances performance in dialysis centers. The study highlighted the importance of buffer type due to its effect on hypotension.

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