Publications by authors named "M Molaie"

22 Publications

Correction: COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication.

J Med Internet Res 2021 Mar 29;23(3):e28926. Epub 2021 Mar 29.

Data Science Group, Institute for Basic Science, Daejeon, Republic of Korea.

[This corrects the article DOI: 10.2196/23272.].
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http://dx.doi.org/10.2196/28926DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042538PMC
March 2021

COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication.

J Med Internet Res 2021 03 16;23(3):e23272. Epub 2021 Mar 16.

Data Science Group, Institute for Basic Science, Daejeon, Republic of Korea.

Background: COVID-19, caused by SARS-CoV-2, has led to a global pandemic. The World Health Organization has also declared an infodemic (ie, a plethora of information regarding COVID-19 containing both false and accurate information circulated on the internet). Hence, it has become critical to test the veracity of information shared online and analyze the evolution of discussed topics among citizens related to the pandemic.

Objective: This research analyzes the public discourse on COVID-19. It characterizes risk communication patterns in four Asian countries with outbreaks at varying degrees of severity: South Korea, Iran, Vietnam, and India.

Methods: We collected tweets on COVID-19 from four Asian countries in the early phase of the disease outbreak from January to March 2020. The data set was collected by relevant keywords in each language, as suggested by locals. We present a method to automatically extract a time-topic cohesive relationship in an unsupervised fashion based on natural language processing. The extracted topics were evaluated qualitatively based on their semantic meanings.

Results: This research found that each government's official phases of the epidemic were not well aligned with the degree of public attention represented by the daily tweet counts. Inspired by the issue-attention cycle theory, the presented natural language processing model can identify meaningful transition phases in the discussed topics among citizens. The analysis revealed an inverse relationship between the tweet count and topic diversity.

Conclusions: This paper compares similarities and differences of pandemic-related social media discourse in Asian countries. We observed multiple prominent peaks in the daily tweet counts across all countries, indicating multiple issue-attention cycles. Our analysis identified which topics the public concentrated on; some of these topics were related to misinformation and hate speech. These findings and the ability to quickly identify key topics can empower global efforts to fight against an infodemic during a pandemic.
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http://dx.doi.org/10.2196/23272DOI Listing
March 2021

A Knowledge-Based Modality-Independent Technique for Concurrent Thigh Muscle Segmentation: Applicable to CT and MR Images.

J Digit Imaging 2020 10;33(5):1122-1135

Control and Intelligent Processing Center of Excellence, School of Electrical and Computer engineering, University College of Engineering,, University of Tehran, North Kargar St., Tehran, Iran.

The mass of the lower extremity muscles is a clinically significant metric. Manual segmentation of these muscles is a time-consuming task. Most of the segmentation methods for the thigh muscles are based on statistical models and atlases which need manually segmented datasets. The goal of this work is an automatic segmentation of the thigh muscles with only one initial segmented slice. A new automatic method is proposed for concurrent individual thigh muscles segmentation using a hybrid level set method and anatomical information of the muscles. In the proposed method, the muscle regions are extracted by the Fast and Robust Fuzzy C-Means Clustering (FRFCM) method, and then a contour is determined for each muscle which changes according to the muscle shape variation through its length. The anatomical information is used to control the contours variations and to refine the final boundaries. The method was validated by 22 CT datasets. The average dice similarity coefficient (DSC) of the method for individual muscle segmentation with one and two initial slices were 89.29 ± 2.59 (%) and 91.77 ± 1.87 (%), respectively. Also, the average symmetric surface distances (ASSDs) were 0.93 ± 0.29 mm and 0.64 ± 0.18 mm. Furthermore, applying to ten MRI datasets, the average DSC and ASSD for muscles were 90.9 ± 2.61 (%) and 0.71 ± 0.33 mm, respectively. The quantitative and intuitive results of the proposed method show the effectiveness of this method in segmentation of large and small muscles in CT and MR images. The consumed computation time is lower than the previous works, and this method does not need any training datasets.
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http://dx.doi.org/10.1007/s10278-020-00354-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7649843PMC
October 2020

Effects of a combination of Nigella sativa and Vitex agnus-castus with citalopram on healthy menopausal women with hot flashes: results from a subpopulation analysis.

Gynecol Endocrinol 2019 Jan 21;35(1):58-61. Epub 2018 Aug 21.

a Department of Clinical Pharmacy, Faculty of Pharmacy, Pharmaceutical Science Branch , Islamic Azad University, IAUPS , Tehran , Iran.

The goal of the current study was to evaluate the efficiency of a phytotherapeutic intervention consisting of a combination of Nigella sativa and Vitex agnus-castus with citalopram in the control of hot flashes in healthy menopausal women. An 8 week, double-blind, randomized, placebo-controlled study was performed among 46 women aged between 40 and 60 years experiencing an average of more than four hot flashes per day recruited during July 2016 to June 2017. Data on severity of vasomotor symptoms were collected at the end of the eighth week. Herbal medication or placebo capsules were administered once daily in morning. At the end of the 8-week treatment period, analyses of covariance demonstrated the superiority of herbal combination with citalopram over placebo and citalopram for three MENQOL domain scores including vasomotor (p < .001), physical (p = .036), psychosocial (p = .001) but no significant differences were observed in terms of sexual function (p = .231). Based on the results, the addition of a combination of N. sativa and V. agnus-castus to the citalopram may be a potential clinical application for improving therapeutic outcomes. Larger randomized, controlled trials are also warranted for further investigations of these symptoms.
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http://dx.doi.org/10.1080/09513590.2018.1499086DOI Listing
January 2019

Artificial neural networks: powerful tools for modeling chaotic behavior in the nervous system.

Front Comput Neurosci 2014 9;8:40. Epub 2014 Apr 9.

Department of Physics, University of Wisconsin Madison, Wisconsin, WI, USA.

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http://dx.doi.org/10.3389/fncom.2014.00040DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3988362PMC
April 2014