M
Marzieh Esmaeili
Researcher at Tehran University of Medical Sciences
Publications - 11
Citations - 426
Marzieh Esmaeili is an academic researcher from Tehran University of Medical Sciences. The author has contributed to research in topics: Computer science & Mammography. The author has an hindex of 3, co-authored 7 publications receiving 95 citations.
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Journal ArticleDOI
The mental health of healthcare workers in the COVID-19 pandemic: A systematic review.
Maryam Vizheh,Mostafa Qorbani,Seyed Masoud Arzaghi,Salut Muhidin,Zohreh Javanmard,Marzieh Esmaeili +5 more
TL;DR: All research carried out on the mental health status of health care workers (HCWs) to bring policymakers and managers’ attention is reviewed to recommend the supportive, encouragement & motivational, protective, and training & educational interventions.
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Characteristics of Children With Kawasaki Disease-Like Signs in COVID-19 Pandemic: A Systematic Review
Parham Mardi,Marzieh Esmaeili,Parisa Iravani,Mohammad Esmail Abdar,Kumars Pourrostami,Mostafa Qorbani +5 more
TL;DR: In this paper, a comprehensive search was carried out systematically through PubMed, Scopus, and Web of Science (WoS), medRxiv, and bioRXiv by two reviewers independently for all studies or preprints data on the demographic, laboratory, and clinical characteristics of children with K.D-like signs during the COVID-19 outbreak.
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Surgical Patients Follow-Up by Smartphone-Based Applications: A Systematic Literature Review.
Tayebeh Baniasadi,Marjan Ghazisaeedi,Mehdi Hassaniazad,Sharareh R. Niakan Kalhori,Mehraban Shahi,Marzieh Esmaeili +5 more
TL;DR: It was showed that mHealth-based interventions have potential that may support better management of post-discharge systematic follow-up of surgery patients.
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Supporting colorectal cancer survivors using eHealth: a systematic review and framework suggestion.
Seyed Mohammad Ayyoubzadeh,Sharareh R. Niakan Kalhori,Mohammad Shirkhoda,Niloofar Mohammadzadeh,Marzieh Esmaeili +4 more
TL;DR: In this article, the authors conducted a systematic review of eHealth systems for colorectal cancer survivors in the past two decades, and the search was limited to 20 years (from 19 January 1999 to 19 January 2019) and the results were tabulated and represented as a framework.
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Prediction of Breast Cancer using Machine Learning Approaches
TL;DR: Combining multiple risk factors in modeling for breast cancer prediction could help the early diagnosis of the disease with necessary care plans and also help the management of different data and intelligent systems based on multiple factors for predicting breast cancer are effective in disease management.