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  • دکتری (1370)

    تحقیق در عملیات

    تنسی، آمریکا

  • کارشناسی‌ارشد (1366)

    تحقیق در عملیات

    تنسی، ناکس ویل، آمریکا

  • مهندسی سیستم‌های سلامت اینترنت سلامت(Healthcare IOT) سلامت همراه(m Health) سلامت ناب(Lean Healthcare) بهینه یابی شبکه و مسیریابی
  • (Data Analytics): واکافت داده، شبكه اجتماعی، متن، پایگاه داده

    داده ای یافت نشد

    ارتباط

    رزومه

    Determining the Level of Importance of Variables in Predicting Kidney Transplant Survival Based on a Novel Ranking Method.

    Nasrin Taherkhani, Mohammad Mehdi Sepehri, Roghaye Khasha, Shadi Shafaghi
    Journal PapersTransplantation , 2021 January 27, {Pages }

    Abstract

    BackgroundKidney transplantation is the best alternative treatment for end-stage renal disease (ESRD). In order to optimal use of donated kidneys, graft predicted survival can be used as a factor to allocate kidneys. The performance of prediction techniques is highly dependent on the correct selection of predictors. Hence, the main objective of this research is to propose a novel method for ranking the effective variables for predicting the kidney transplant survival.MethodsFive classification models were used to classify kidney recipients in long-and short-term survival classes. Synthetic minority oversampling (SMOTE) and random under sampling (RUS) were used to overcome the imbalanced class problem. In dealing with missing values, 2 appro

    Dynamics of customer segments: A predictor of customer lifetime value

    Abdolreza Mosaddegh, Amir Albadvi, Mohammad Mehdi Sepehri, Babak Teimourpour
    Journal PapersExpert Systems with Applications , Volume 172 , 2021 June 15, {Pages 114606 }

    Abstract

    Most studies in the literature have focused on past behavior of customers to measure customer lifetime value, however, the rapid developments of technology and products make new conditions that cannot be predicted by past records anymore. In the era of new media and social networks, customers’ needs and expectations change fast which lead to instability of customer lifetime value.In the present study, we studied the dynamics of bank customers through value segments using big data analytics. By mining patterns of associations between customer transitions, we found six major categories, including the pattern of Local Leaders whose transitions are repeated by some follower groups within next two periods. Such results suggest that the dynamic

    The association of vitamin-D level with catheter-related-thrombosis in hemodialysis patients: A data mining model

    Zhaleh Rahimi, Neda Abdolvand, Mohammad Mehdi Sepehri, Morteza Khavanin Zadeh
    Journal PapersThe Journal of Vascular Access , 2021 March 14, {Pages https://doi.org/10.1177/1129729821100115 }

    Abstract

    Purpose:This study aims to investigate the association of different risk factors including vitamin-D level with catheter-related-thrombosis in hemodialysis patients by applying data mining techniques.Methods:This study used the retrospectively approach and was done based on the CRISP-DM framework. The data of 1048 hemodialysis patients of Hasheminejad Kidney Center whose first catheterization was between 2014 and 2019 was used for analysis. In this study, patients with a previous history of deep venous thrombosis, thrombophilic condition, and undergone anticoagulant therapy were excluded. The decision tree J48 in WEKA software was used for modeling. The K-fold cross-validation method was also used to evaluate the classification performance.

    Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study

    Toktam Khatibi, Elham Hanifi, Mohammad Mehdi Sepehri, Leila Allahqoli
    Journal PapersBMC pregnancy and childbirth , Volume 21 , Issue 1, 2021 December , {Pages 17-Jan }

    Abstract

    Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to predict stillbirth from livebirth and discriminate stillbirth before and during delivery and rank the features. A two-step stack ensemble classifier is proposed for classifying the instances into stillbirth and livebirth at the first step and then, classifying stillbirth before delivery from stillbirth during the labor at the second step. The proposed SE has two consecutive layers including the same classifiers. The base classifiers in each layer are decision tree, Gradient boosting classifier, logistics regression, random forest and support vector machines which are trained independently and aggregated ba

    A Predictive Framework in Healthcare: Case Study on Cardiac Arrest Prediction

    Samaneh Layeghian Javan, Mohammad Mehdi Sepehri
    Journal PapersArtificial Intelligence in Medicine , 2021 May 7, {Pages https://doi.org/10.1016/j.artmed.2021.10 }

    Abstract

    Data-driven healthcare uses predictive analytics to enhance decision-making and personalized healthcare. Developing prognostic models is one of the applications of predictive analytics in medical environments. Various studies have used machine learning techniques for this purpose. However, there is no specific standard for choosing prediction models for different medical purposes. In this paper, the ISAF framework was proposed for choosing appropriate prediction models with regard to the properties of the classification methods. As one of the case study applications, a prognostic model for predicting cardiac arrests in sepsis patients was developed step by step through the ISAF framework. Finally, a new modified stacking model produced the

    A regionalization model to increase equity of access to maternal and neonatal care services in Iran

    Z Mohammadi Daniali, MM Sepehri, F Movahedi Sobhani, ...
    Journal Papers , , {Pages }

    Abstract

    Presenting a model for the optimal allocation of human resources to operational processes using the Markowitz model: A case study in urology unit at a kidney center

    B Ostadi, M Ebrahimi-Sadrabadi, A Husseinzadeh Kashan, MM Sepehri
    Journal Papers , , {Pages }

    Abstract

    Determining the Level of Importance of Variables in Predicting Kidney Transplant Survival Based on a Novel Ranking Method

    N Taherkhani, MM Sepehri, R Khasha, S Shafaghi
    Journal Papers , , {Pages }

    Abstract

    Detecting asthma control level using feature-based time series classification

    R Khasha, MM Sepehri, N Taherkhani
    Journal Papers , , {Pages }

    Abstract

    An efficient centralized master echocardiography schedule in a distributed hospital/clinic network

    Delaram Chaghazardy, Seyed Hessameddin Zegordi, Mohammad Mehdi Sepehri, Hassan Aghajani
    Journal PapersJournal of Industrial and Systems Engineering , 2020 April 24, {Pages }

    Abstract

    Appointment scheduling systems are applied in a broad variety of healthcare environments to reduce costs and increase quality of services. This study is concerned with the problem of appointment scheduling in a distributed multi-hospital network of echocardiography departments. In this paper, a centralized master schedule is presented to maximize profit margin through maximizing the number of performed echoes and minimizing overtime. Developing such a schedule requires handling shift scheduling and capacity allocation problems simultaneously. Based on real-world settings, a mixed integer linear programming model is proposed for the research problem. Since this model requires a large amount of time and memory to provide good solutions, and f

    An Assessment Model for Hospital Resilience according to the Simultaneous Consideration of Key Performance Indicators: A System Dynamics Approach

    Mohammad Pishnamazzadeh, Mohammad Mehdi Sepehri, Bakhtiar Ostadi
    Journal PapersPerioperative Care and Operating Room Management , 2020 May 28, {Pages https://doi.org/10.1016/j.pcorm.2020.100 }

    Abstract

    BackgroundGlobalization allows the effects of disruptions to cascade in the systems rapidly and a small disruption could lead to a broad catastrophe. Nowadays, disruptions are becoming more unpredictable, more frequent and more damaging. Hospitals are critical facilities which play an important role after disruptions. Number of deaths and injuries from disasters depends heavily on how hospitals serve people. Therefore, assuring the proper performance of hospitals under disruption is an important issue. Our approach to improve hospital performance is modelling the performance from resilience engineering perspective.MethodsFirst step towards building or designing a resilient organization is assessment and based on that a set of strategies or

    Designing a cost-driven mechanism to reduce cancellation of elective surgeries

    Kamand Hajiaghapour, Mohammad Mehdi Sepehri, Roghaye Khasha
    Journal PapersPerioperative Care and Operating Room Management , Volume 18 , Issue March 2020, 100085, 2020 January 7, {Pages 11 }

    Abstract

    BackgroundA significant portion of each country's budget is assigned to its health care system annually. Given the current economic conditions, saving costs is a key issue. Therefore, any situation that leads to lower efficiency and higher costs should be remedied. With much of the hospitals' budgets spent on operating rooms, it is important to use strategies to increase their efficiency and quality. The purpose of this study is to design a mechanism to reduce the cancellation of elective surgical procedures, which incurs considerable costs.MethodsTo this end, the data gathered from an educational hospital in Tehran were evaluated. The reasons for the surgical cancellations were determined through data analysis and process identification. S

    Effects and challenges of Health Transformation Plan in public health: views of public health providers.

    Seyed Hadi Hosseini, Amirhossein Takian, Mohammad Mehdi Sepehri, Mehdi Yasseri, Batoul Ahmadi
    Journal PapersDilemas Contempor?neos: Educaci?n, Pol?tica y Valores , Volume 7 , Issue 2, 2020 January 1, {Pages }

    Abstract

    English In every Health Transformation Plan, operational challenges and the distance from the primary goals need to be identified. So, the main purpose of this study was obtaining effects and challenges of plan observed by healthcare providers. Participants of this conventional quali? tative method of content analysis study were 45 supervisors and employees who affiliated to Tehran University of Medical Sciences. The challenges differed according to the study places (Community Health Centers, Health Posts and Health Homes) in Work contracts, Integrated Health System, Financial Management, Intermediary companies, Quality, Supervision, Payments, Locations and Family Physician Plan. To effectively implement a health plan and achieve its goals,

    Studying the Effects of Systemic Inflammatory Markers and Drugs on AVF Longevity through a Novel Clinical Intelligent Framework

    Akram Nakhaei, Mohammad Mehdi Sepehri, Pejman Shadpour, Toktam Khatibi
    Journal PapersIEEE Journal of Biomedical and Health Informatics , 2020 April 13, {Pages 10.1109/JBHI.2020.2986183 }

    Abstract

    Although arteriovenous fistula is the preferred vascular access method, it has challenges in three phases of planning, maturation, and maintenance. We looked at the root of fistula challenges in the maintenance phase and found traces of inflammation. We investigated the role of systemic inflammation in the maintenance phase to understand its effects on post-maturation function and extract knowledge to help extend fistula longevity. Previous studies on fistula longevity have focused entirely on statistical tests. Since these tests put limitations on data, we also used a data mining framework for data analysis. For predictive analysis, we used the decision tree, random forest, and support vector machines. For inferential analysis, we used the

    Reallocation of unoccupied beds among requesting wards

    Mohammad Pishnamazzadeh, Mohammad Mehdi Sepehri, Atefeh Panahi, Parisa Moodi
    Journal PapersJournal of Ambient Intelligence and Humanized Computing , 2020 January , {Pages Accepted, to be published }

    Abstract

    Quality Improvement through Intensive Care Registries: The Value of Big Data in Clinical Decision Making

    Ali Sanaei, Mohammad Mehdi Sepehri
    Journal PapersArchives of Anesthesiology and Critical Care , Volume 6 , Issue 1, 2020 January , {Pages 33-40 }

    Abstract

    Background: Quality of Intensive care has got more attention in case of the high cost of healthcare and the potential for harm. Poor-quality care causes high cost and quality improvement initiatives in the ICU lead to an improvement in outcomes as well as a decrease in costs. One of the crucial tools that allow physicians and nurses to monitor change in a quality improvement effort is the development of an electronic database for data collection and reporting. The objective of Intensive Care Registries is to create a high-quality registry of patients through a collaboration of academic health centers performing uniform data collection with the purpose of improving the quality and accuracy of healthcare decisions and provide a data-driven cl

    Designing a novel hybrid healthcare teleconsultation network: a benchtop study of telepathology in Iran and a systematic review

    Mohammad Mahdi Taghipour, Mohammad Mehdi Sepehri
    Journal Papers , Volume 20 , Issue 1, 2020 December , {Pages 11-Jan }

    Abstract

    Growing demand for medical services has increased patient waiting time due to the limited number or unbalanced distribution of healthcare centers. Healthcare teleconsultation networks are one of the potentially powerful systems to overcome this problem. Medical pathology can hugely benefit from teleconsultation networks because having second opinions is precious for many cases; however, resource planning (i.e., assignment and distribution of pathology consultation requests) is challenging due to bulky medical images of patients. This results in high setup and operational costs. The aim of this study is to design an optimal teleconsultation network for pathology labs under the supervision of medical sciences universities in Tehran, Iran. To

    Equitable distribution of neonatal intensive care unit: a healthcare planning case study

    Zahra Mohammadi Daniali, Mohammad Mehdi Sepehri, Farzad Movahedi Sobhani, Mohammad Heidarzadeh
    Journal PapersInternational Journal of Hospital Research , Volume 9 , Issue 2, 2020 August 1, {Pages }

    Abstract

    Background and objectives: The regionalization is a suitable approach to reduce the cost of health services and to increase the number of patients covered by special services. Since the establishment of the Neonatal Intensive Care Unit (NICU) needs expensive equipment and experts, it is critical to find the optimal number and location for NICU beds and referral networks. Methods: The geographical access to NICU beds was investigated by collecting the annual demand and the distance between cities at first. The demand consisted of the number of neonates that were born under 32 weeks of gestational age or having less than 1500 gram birth weight in one province of Iran. Next, the location of the available hospital has defined on the map. A maxi

    Asthma Control Level Assessment by Moving from the Current Reactive Care Models into A Preventive Approach Based On Fuzzy Clustering and Classification Algorithms

    Roghaye Khasha, Mohammad Mehdi Sepehri, Nasrin Taherkhani
    Journal PapersJournal of Payavard Salamat , Volume 14 , Issue 3, 2020 July 28, {Pages }

    Abstract

    Materials and Methods: Based on this objective, we collected the data of 96 Asthma patients within a 9-month period from a specialized hospital for pulmonary diseases in Tehran. Then we classified the Asthma control level by fuzzy clustering and different types of data mining method within a multivariate dataset with the multi-class response variable.Results: Our best model resulting from the balancing operations and feature selection on data have yielded the accuracy of 88%.Conclusion: Our proposed model can be applied in electronic Asthma self-care systems to support the decision in real time and personalized warnings on the possible deterioration of Asthma control. Such tools can centralize the Asthma treatment from the current reactive

    How a cardiovascular patient education system can be improved: Introducing a novel model for identifying hospital educational challenges and solutions

    Atiyeh Saboktakin, Mohammad Mehdi Sepehri, Roghaye Khasha
    Journal Papers , 2020 August 1, {Pages }

    Abstract

    Background: Cardiovascular diseases (CVDs) have always been considered by healthcare 2 specialists for different reasons, including extensive prevalence, high cost, chronicity, and high risk of 3 death. the recovery from CVDs is highly influenced by the behavior and lifestyle. As a result, it seems 4 necessary to train and develop special abilities for patients and their companions, the development of 5 efficient and effective training systems should be considered by healthcare specialists. 6Methods: Hence, in this study, an existing training system for cardiovascular patients is reviewed, 7 and using field observation and targeted interviews with hospital experts, all aspects of its training process, 8 including involved components, inputs

    دروس نیمسال جاری

    • كارشناسي ارشد
      بهينه سازي و علم داده ها ( واحد)
      دانشکده مهندسی صنایع و سیستم‌ها، گروه آمار كاربردي
    • كارشناسي ارشد
      بهبود فرايند و كيفيت در سلامت ( واحد)
    • كارشناسي ارشد
      انفورماتيك در سلامت ( واحد)

    دروس نیمسال قبل

    • كارشناسي ارشد
      مدل سازي داده محور در سلامت ( واحد)
      دانشکده مهندسی صنایع و سیستم‌ها، گروه مهندسي صنايع
    • كارشناسي ارشد
      روش تحقيق ( واحد)
    • دكتري
      نظريه شبكه ( واحد)
    • كارشناسي ارشد
      كارورزي مهندسي سيستم هاي سلامت 1 ( واحد)
    • 1397
      محمدي, فاطمه
      ارائه مدل ساختارمند سازمان مردم نهاد ديابت با رويكرد تجميع ساختارهاي موجود
    • 1397
      سيفي, شاهده
    • 1398
      سيديان, مهديه سادات
    • 1398
      كياني, درسا
    • 1398
      حسين پناهي, سوما
    • 1398
      تقوي, فرناز
    • 1398
      رضايي, معصومه
    • 1398
      نيك روز, محمدرضا
    • 1392
      سعيديان, معصومه
      مدل همنواخت سازي منابع اكوسيستم اتاق عمل - طراحي وحل
    • 1394
      نخعي, اكرم
    • 1395
      پيشنماززاده, محمد
    • 1396
      برنا, مهدي رضا
    • عضو کمیته تخصصی فناوری اطلاعات و آموزش الکترونیکی
    • مدیر گروه فناوری اطلاعات
    • رئیس پژوهشکده فناوری اطلاعات
    • عضو کمیته تخصصی گسترش فنی و مهندسی
    • عضو کمیته ارزیابی و بهینه سازی عملکرد دانشگاه
    • عضو شورای نظارت، ارزیابی و بهینه سازی عملکرد دانشگاه
    • عضو کمیته انتخاب اعضای هیات علمی نمونه دانشگاه در سالهای 88 الی 90
    • عضو شورای نشانها
    • مدیر دفتر امور هیات علمی دانشگاه تربیت مدرس
    • عضو هیات ممیزه دانشگاه تربیت مدرس
    • عضو کمیته تخصصی گسترش فنی و مهندسی
    • عضو هیئت تحریریه فصلنامه مدیریت توسعه فناوری
    • عضو کمیته یادگیری الکترونیکی
    • مدیر گروه مهندسی صنایع
    • عضو کمیته تخصصی گسترش فنی و مهندسی دانشگاه آزاد اسلامی
    • عضو هیات تحریریه پژوهشنامه حمل و نقل
    • رئیس مرکز کامپیوتر دانشگاه
    • رئیس بخش مهندسی صنایع
    • سرپرست کمیته مهندسی صنایع و عضو گروه فنی و مهندسی
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