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Decision Modeling for Diagnosis and Screening of Ovarian Epithelial Cancer
Reza Safdari, Leila Shahmoradi, Marjan Daneshvar, Elmira Pourtorkan, Mersa Gholamzadeh,
Volume 12, Issue 1 (5-2018)
Abstract
Background and Aim: The Ovarian epithelial cancer is one of the most deadly types of cancers in women.Thus, the purpose of this study was to investigate the most effective factors in predicting and detecting Ovarian cancer in the form of a decision tree to facilitate the Ovarian cancer diagnosis.
Materials and Methods: The present study was a descriptive-developmental study. The main research tool applied in this study was a checklist which was designed based on the medical records, published studies, scientific references, and expert consultation.To determine the content validity of the checklist, the CVR method was applied. Next, survey research was done with aid of Likert-based checklist based on expert opinions in gynecology. Finally, to develop the decision tree, the results of the expert survey were analyzed and the final model was implemented based on the survey results.
Results: The data elements of final decision tree were derived from the result of expert surveys, guidelines, clinical pathways and strategies in context of diagnosis and screening of Ovarian cancer. The leaf nodes in the tree include different types of tumor markers, following up, therapeutic measures, and referrals. The accuracy of the decision tree was approved by the experts. The most important tumor markers that obtained from the decision model in this study were CA19-9, ROMA (CA125 + HE4) and CEA.
Conclusion: Clinical decision models can provide specific diagnosis and therapeutic suggestions by creating patient information integration framework. The model developed in this study can improve the diagnosis of epithelial Ovarian cancer considerably by facilitating decision making.

The Effectiveness Dimensions of Intelligent Secretariat in Tehran University of Medical Sciences
Maryam Ahmadi, Mashallah Torabi, Maryam Goodarzi, Hamideh Hamidi, Samira Elmi, Fatemeh Golmahi, Samira Mortezaie, Parisa Nezari,
Volume 13, Issue 4 (Oct & Nov 2019)
Abstract
Background and Aim: The purpose of this study was to introduce a new model for indicator of letters in office automation of Tehran University of Medical Sciences.
Materials and Methods: The present study was an applied research and a developmental study in which old automation method has been modified to new model. Regarding to the dispersion of codes assigned to letters, there was no specific order in the codes of both old and new units defined in the system, and firstly, the letter indicators in the office automation system of university in combination with letters and numbers was done without classification, the decision was made to correct it in the office automation system. In new model, numbering the correspondence based on frequency of each university unit's subdivision was described and proposed model was presented.
Results: According to the new numerical model, integrated codes were assigned which were entirely numerical or the combination of numbers. Due to the abundance of units covered by the university, the research centers allocate the largest number to themselves. Therefore, a larger range of indicator codes for these units was considered than for other sections.
Conclusion: This model provides a new model for implementation of office automation indicator code in Tehran University of Medical Sciences and facilitates the search of letters based on the defined number. 

The Effect of Eight Weeks Aerobic Training on Serum Ferritin Level, Glycemic and Lipid Indices in Women with Type 2 Diabetes
Atefeh Helmi Siyasi, Nahid Bijeh, Elham Hakak Dokht, Gholam Rasul Mohammad Rahimi,
Volume 15, Issue 2 (Jun & Jul 2021)
Abstract
Background and Aim: Recent studies indicate that increased body iron stores have been associated with the development of glucose intolerance and type 2 Diabetes. Ferritin is the most important iron storage protein in the body, which is used to evaluate disorders associated with iron metabolism. The aim of this study was to examine the effect of eight weeks of aerobic training on serum ferritin level, glycemic and lipid indices in women with type 2 Diabetes.
Material and Methods: Twenty Diabetic women aged 45-55 years were selected voluntarily and divided into experimental (n=10) and control (n=10) groups. The experimental group participated in the aerobic training program for eight weeks, three 60-minutes sessions per week with an intensity of 55-65% of heart rate reserve. The control group did not participate in any activity during the intervention period. Serum ferritin, glycemic and lipid indices were evaluated before and after eight weeks and then data were analyzed by SPSS software.
Results: Ferritin (P=0.012), insulin (P=0.004), fasting glucose (P=0.041), insulin resistance index (P=0.012), total cholesterol (P=0.041), and triglyceride (P=0.005) significantly decreased, while the mean of HDL(P=0.012) significantly increased in the experimental group. Moreover, the results showed that changes in ferritin (P=0.002), insulin (P=0.014), insulin resistance index (P=0.001) and TG (P=0.010) were statistically significant between the experimental and control groups.
Conclusion: Women with type 2 Diabetes can benefit from moderate-intensity aerobic exercise programs to improve their glycemic and lipid profile, as well as iron metabolism abnormalities.

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