Journal of Education and Health Promotion

. Vahid Falahati; . Ali Ghasemi; . Kazem Ghaffari; . Aziz Eghbali; . Sanaz Khodabakhshi; . Amir Almasi‑Hashiani; . Bahman Sadeghi‑Sedeh; . Mostafa Shanbehzadeh

Volume 12, Issue 10 , November 2022, , Pages 1-7

Abstract

BACKGROUND: Iron deficiency anemia (IDA) is one of the most common anemias, especially inchildren 4–23 months. Therefore, prophylaxis is necessary to improve iron status as well ... Read More

Developing the breast cancer risk prediction system using hybrid machine learning algorithms

. Mohammad R. Afrash; . Azadeh Bayani; . Mostafa Shanbehzadeh; . Mohammadkarim Bahadori; . Hadi Kazemi‑Arpanahi

Volume 12, Issue 7 , August 2022, , Pages 1-12

Abstract

BACKGROUND: Breast cancer (BC) is the most common cause of cancer‑related deaths in womenglobally. Currently, many machine learning (ML)‑based predictive models have been established ... Read More BACKGROUND: Breast cancer (BC) is the most common cause of cancer‑related deaths in womenglobally. Currently, many machine learning (ML)‑based predictive models have been established toassist clinicians in decision making for the prediction of BC. However, preventing risk factor formationeven with having healthy lifestyle behaviors or preventing disease at early stages can significantlylead to optimal population‑wide BC health. Thus, we aimed to develop a prediction model by using agenetic algorithm (GA) incorporating several ML algorithms for the prediction and early warning of BC.MATERIAL AND METHODS: The data of 3168 healthy individuals and 1742 patient case recordsin the BC Registry Database in Ayatollah Taleghani hospital, Abadan, Iran were analyzed. First, amodified hybrid GA was used to perform feature selection and optimization of selected features.Then, with the use of selected features, several ML algorithms were trained to predict BC. Afterward,the performance of each model was measured in terms of accuracy, precision, sensitivity, specificity,and receiver operating characteristic (ROC) curve metrics. Finally, a clinical decision support systembased on the best model was developed.RESULTS: After performing feature selection, age, consumption of dairy products, BC family history,breast biopsy, chest X‑ray, hormone therapy, alcohol consumption, being overweight, having children,and education statuses were selected as the most important features for prediction of BC. Theexperimental results showed that the decision tree yielded a superior performance than other MLmodels, with values of 99.3%, 99.5%, 98.26% for accuracy, specificity, and sensitivity, respectively.CONCLUSION: The developed predictive system can accurately identify persons who are at elevatedrisk for BC and can be used as an essential clinical screening tool for the early prevention of BC andserve as an important tool for developing preventive health strategies.

Using logistic regression to develop a diagnostic model for COVID‑19: A single‑center study

. Raoof Nopour; . Mostafa Shanbehzadeh; . Hadi Kazemi‑Arpanahi

Volume 12, Issue 5 , June 2022, , Pages 1-6

Abstract

BACKGROUND: The main manifestations of coronavirus disease‑2019 (COVID‑19) are similarto the many other respiratory diseases. In addition, the existence of numerous uncertainties ... Read More

Developing an artificial neural network for detecting COVID‑19 disease

. Mostafa Shanbehzadeh; . Raoof Nopour; . Hadi Kazemi-Arpanahi

Volume 12, Issue 1 , January 2022, , Pages 1-10

Abstract

BACKGROUND: From December 2019, atypical pneumonia termed COVID‑19 has been increasingexponentially across the world. It poses a great threat and challenge to world health and the ... Read More

Performance analysis of data mining algorithms for diagnosing COVID‑19

. Raoof Nopour; . Hadi Kazemi‑Arpanahi; . Mostafa Shanbehzadeh; . Akbar Azizifar

Volume 11, Issue 10 , November 2021, , Pages 1-8

Abstract

BACKGROUND: An outbreak of atypical pneumonia termed COVID‑19 has widely spread all overthe world since the beginning of 2020. In this regard, designing a prediction system for the ... Read More

Performance evaluation of selected machine learning algorithms for COVID‑19 prediction using routine clinical data: With versus Without CT scan features

. Mostafa Shanbehzadeh; . Hadi Kazemi-Arpanahi; . Azam Orooji; . Sara Mobarak; . Saeed Jelvay

Volume 11, Issue 7 , August 2021, , Pages 1-11

Abstract

BACKGROUND: Given coronavirus disease (COVID‑19’s) unknown nature, diagnosis, and treatmentis very complex up to the present time. Thus, it is essential to have a framework ... Read More

Systematic review on telemedicine platforms in lockdown periods: Lessons learned from the COVID‑19 pandemic

. Mostafa Shanbehzadeh; . Hadi Kazemi-Arpanahi; . Sasan Ghorbani Kalkhajeh; . Gholam Basati

Volume 11, Issue 5 , June 2021, , Pages 1-10

Abstract

With the onset of the coronavirus disease 2019 (COVID‑19) outbreak, the transformation of the caredelivery model from conventional in-person (face to face) to largely virtual or remote ... Read More

Notifiable diseases interoperable framework toward improving Iran public health surveillance system: Lessons learned from COVID‑19 pandemic

. Mostafa Shanbehzadeh; . Hadi Kazemi-Arpanahi; . Ali Asghar Valipour; . Atefeh Zahedi

Volume 11, Issue 4 , May 2021, , Pages 1-11

Abstract

BACKGROUND: Direct transmission of notifiable disease information in a real‑time and reliable wayto public health decision‑makers is imperative for early identification of epidemiological ... Read More

Data integration in cardiac electrophysiology ablation toward achieving proper interoperability in health information systems

. Hadi Kazemi-Arpanahi; . Mostafa Shanbehzadeh; . Esmat Mirbagheri; . Abdolvahab Baradaran

Volume 10, Issue 10 , October 2020, , Pages 1-9

Abstract

INTRODUCTION: Providing information exchange and collaboration between isolated informationsystems (ISs) is essential in the health‑care environments. In this context, we aimed to ... Read More

Coronavirus disease 2019 (COVID-19) surveillance system: Development of COVID-19 minimum data set and interoperable reporting framework

. Mostafa Shanbehzadeh; . Hadi Kazemi-Arpanahi; . Komeil Mazhab-Jafari; . Hamideh Haghiri

Volume 10, Issue 8 , August 2020, , Pages 1-11

Abstract

INTRODUCTION: The 2019 coronavirus disease (COVID‑19) is a major global health concern. Jointefforts for effective surveillance of COVID‑19 require immediate transmission of reliable ... Read More

Improving hypertension surveillance from a data management prospective: Data requirements for implementation of population-based registry

. Mostafa Shanbehzadeh; . Hadi Kazemi-Arpanahi; . Arezo Arzani-Birgani; . Azimeh Karimyan; . Fatemeh Mobasheri

Volume 10, Issue 6 , June 2020, , Pages 1-8

Abstract

BACKGROUND: Hypertension (HTN) has become a major public health problem which can causeserious complications when it is not well-controlled. Prevention and effective care of HTN requirea ... Read More

Designing a communication protocol for acquired immunodeficiency syndrome information exchange

. Mostafa Shanbehzadeh; . Jahangir Abdi; . Maryam Ahmadi

Volume 9, Issue 5 , May 2019, , Pages 1-8

Abstract

INTRODUCTION: Interoperability will provide similar understanding on the meaning of communicatedmessages to intelligent systems and their users. This feature is essential for controlling ... Read More

Volume 13 (2023)

Volume 12 (2022)

Volume 11 (2021)

Volume 10 (2020)

Volume 9 (2019)

Volume 8 (2018)

Volume 7 (2017)

Volume 6 (2016)

Volume 5 (2015)

Volume 4 (2014)

Volume 3 (2013)

Volume 2 (2012)

Volume 1 (1900)

Author = . Mostafa Shanbehzadeh

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