ArticleJournal of infection and public health
Building predictive models for MERS-CoV infections using data mining techniques.
Article in Journal of infection and public health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
- Role of biological Data Mining and Machine Learning Techniques in Detecting and Diagnosing the Novel Coronavirus (COVID-19): A Systematic Review.Journal of medical systems · 2020Pooled it
- Praemonitus praemunitus: can we forecast and prepare for future viral disease outbreaks?FEMS microbiology reviews · 2023Review
- Investigating the performance of machine learning algorithms in predicting the survival of COVID-19 patients: A cross section study of Iran.Health science reports · 2023Article
- Prognosis of COVID-19 patients using lab tests: A data mining approach.Health science reports · 2023Article
- Forecasting COVID-19 cases using time series modeling and association rule mining.BMC medical research methodology · 2022Article
- Modelling Covid-19 infections in Zambia using data mining techniques.Results in engineering · 2022Article
- Supervised Machine Learning Approach to COVID-19 Detection Based on Clinical Data.Medical journal of the Islamic Republic of Iran · 2022Article
- Real-time prediction of COVID-19 patients health situations using Artificial Neural Networks and Fuzzy Interval Mathematical modeling.Applied soft computing · 2021Article
- Classification of SARS-CoV-2 and non-SARS-CoV-2 using machine learning algorithms.Computers in biology and medicine · 2021Article
- Health informatics publication trends in Saudi Arabia: a bibliometric analysis over the last twenty-four years.Journal of the Medical Library Association : JMLA · 2021Article
- Estimation of the Prevalence of Nonalcoholic Fatty Liver Disease in an Adult Population in Northern China Using the Data Mining Approach.Diabetes, metabolic syndrome and obesity : targets and therapy · 2021Article
- Estimation of Diabetes in a High-Risk Adult Chinese Population Using J48 Decision Tree Model.Diabetes, metabolic syndrome and obesity : targets and therapy · 2020Article
- Predictive Data Mining Models for Novel Coronavirus (COVID-19) Infected Patients' Recovery.SN computer science · 2020Article
- Identification of Potential Type II Diabetes in a Chinese Population with a Sensitive Decision Tree Approach.Journal of diabetes research · 2019Article
- Factors associated with recovery delay in a sample of patients diagnosed by MERS-CoV rRT-PCR: A Saudi Arabian multicenter retrospective study.Influenza and other respiratory viruses · 2018Article
- Underlying trend, seasonality, prediction, forecasting and the contribution of risk factors: an analysis of globally reported cases of Middle East Respiratory Syndrome Coronavirus.Epidemiology and infection · 2018Article
- Network Analysis of MERS Coronavirus within Households, Communities, and Hospitals to Identify Most Centralized and Super-Spreading in the Arabian Peninsula, 2012 to 2016.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2018Article
- The predictors of 3- and 30-day mortality in 660 MERS-CoV patients.BMC infectious diseases · 2017Article
- A data mining approach for modeling churn behavior via RFM model in specialized clinics Case study: A public sector hospital in Tehran.Procedia computer science · 2017Article
- Individual and network characteristic associated with hospital-acquired Middle East Respiratory Syndrome coronavirus.Journal of infection and public healthArticle
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRecently, the outbreak of MERS-CoV infections caused worldwide attention to Saudi Arabia. The novel virus belongs to the coronaviruses family, which is responsible for causing mild to moderate colds. The control and command center of Saudi Ministry of Health issues a daily report on MERS-CoV infection cases. The infection with MERS-CoV can lead to fatal complications, however little information is known about this novel virus. In this paper, we apply two data mining techniques in order to better understand the stability and the possibility of recovery from MERS-CoV infections.
methodThe Naive Bayes classifier and J48 decision tree algorithm were used to build our models. The dataset used consists of 1082 records of cases reported between 2013 and 2015. In order to build our prediction models, we split the dataset into two groups. The first group combined recovery and death records. A new attribute was created to indicate the record type, such that the dataset can be used to predict the recovery from MERS-CoV. The second group contained the new case records to be used to predict the stability of the infection based on the current status attribute.
resultsThe resulting recovery models indicate that healthcare workers are more likely to survive. This could be due to the vaccinations that healthcare workers are required to get on regular basis. As for the stability models using J48, two attributes were found to be important for predicting stability: symptomatic and age. Old patients are at high risk of developing MERS-CoV complications. Finally, the performance of all the models was evaluated using three measures: accuracy, precision, and recall. In general, the accuracy of the models is between 53.6% and 71.58%.
conclusionWe believe that the performance of the prediction models can be enhanced with the use of more patient data. As future work, we plan to directly contact hospitals in Riyadh in order to collect more information related to patients with MERS-CoV infections.
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