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Special Issue "Big Data, Decision Models, and Public Health"

Special Issue Editors

Guest Editor
Prof. Dr. Chien-Lung Chan

Dean, Department of Information Management, Yuan Ze University, Taoyuan City, Taiwan
Website | E-Mail
Interests: medical informatics; decision science; big data analytics; public health
Guest Editor
Prof. Dr. Chi-Chang Chang

Chair of Medical Informatics Department, Chung Shan Medical University, Taichung City, Taiwan
Website | E-Mail
Interests: medical informatics; clinical decision analysis; simulation modeling; shared medical decision making

Special Issue Information

Dear colleagues,

In the digital era, the volume and velocity of environmental, population and public health data from a diverse range of sources are growing rapidly. Big data analytics techniques such as statistical analysis, data mining, machine learning and deep learning can be applied to construct innovative decision models. Decision-making based on concrete evidence is critical and has a substantial impact on public health and program implementation. This fact highlights the important role of decision models under uncertainty, including disease control, health intervention, preventive medicine, health services and systems, health disparities and inequalities, and quality of life, etc. With complex decision making, it can be difficult to comprehend and compare the benefits and risks of all available options to make a decision. This Special Issue focuses on the use of big data analytics and forms of public health decision-making based on the decision model, spanning from theory to practice. While working with people’s health and medical information, we also need to commit to scientific integrity issues including people’s privacy, data sharing, bias and uncertainty, research design and statistical inference. Practical experiences and experiments concerning the above issues in big data analytics are also welcome.

Prof. Dr. Chien-Lung Chan
Prof. Dr. Chi-Chang Chang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Big Data Analytics
  • Data Mining, Deep Learning, and Artificial Intelligence
  • Survival Analysis and Health Hazard Evaluations
  • Statistics and Quality of Health/Medical Big Data
  • Intelligent Decision Making Models in Public Health
  • Health Risk Evaluation and Modelling
  • Patient Safety and Outcomes
  • Data-driven Decision Model with Empirical Studies
  • Cloud Computing and Innovative Services
  • Decision Applications in Clinical Issues

Published Papers (2 papers)

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Research

Open AccessArticle
APOE Variant (rs405509) might Modulate the Effect of Sex and Educational Level on Cognitive Impairment Risk in a Taiwanese Population
Int. J. Environ. Res. Public Health 2019, 16(10), 1732; https://doi.org/10.3390/ijerph16101732
Received: 6 March 2019 / Revised: 9 May 2019 / Accepted: 14 May 2019 / Published: 16 May 2019
PDF Full-text (307 KB) | HTML Full-text | XML Full-text
Abstract
Education, sex, and the APOE-rs405509 variant are associated with Alzheimer’s disease and cognitive performance. We investigated if the rs405509 TT, TG, and GG genotypes modulate the effect of sex and education on cognitive impairment in Taiwanese adults. Data on cognitive health (defined by [...] Read more.
Education, sex, and the APOE-rs405509 variant are associated with Alzheimer’s disease and cognitive performance. We investigated if the rs405509 TT, TG, and GG genotypes modulate the effect of sex and education on cognitive impairment in Taiwanese adults. Data on cognitive health (defined by Mini-Mental State Examination (MMSE) scores) and rs405509 were from Taiwan Biobank. Participants included 2105 men and 2027 women with a mean age of 64 years. Education below university level was significantly associated with lower MMSE scores. The odds ratios (ORs) were 1.82; 95% confidence interval (CI) 1.38–2.41 for senior high school, 3.39; 95% CI 2.50–4.59 for junior high school, and 11.94; 95% CI 9.91–15.50 for elementary school and below (p-trend < 0.05). The association between MMSE score and sex was significant only in the lowest educational group (elementary and below), with lower odds of having a low MMSE score in men compared to women (OR = 0.51; 95% CI 0.34–0.77). After stratification by rs405509 genotypes, this association was significant only among TT genotype carriers (OR = 0.481; CI = 0.253–0.915). In conclusion, a significant association between MMSE score and sex was observed in the lowest educational group, especially among carriers of rs405509 TT genotypes. Full article
(This article belongs to the Special Issue Big Data, Decision Models, and Public Health)
Open AccessArticle
Interleukin-3 Polymorphism is Associated with Miscarriage of Fresh in Vitro Fertilization Cycles
Int. J. Environ. Res. Public Health 2019, 16(6), 995; https://doi.org/10.3390/ijerph16060995
Received: 3 February 2019 / Revised: 5 March 2019 / Accepted: 17 March 2019 / Published: 19 March 2019
PDF Full-text (320 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The aim of this study was to examine the association between interleukin (IL) genes polymorphisms and in vitro fertilization (IVF) outcome. A prospective cohort analysis was performed at a Women’s Hospital IVF centre of 1015 female patients undergoing fresh non-donor IVF cycles. The [...] Read more.
The aim of this study was to examine the association between interleukin (IL) genes polymorphisms and in vitro fertilization (IVF) outcome. A prospective cohort analysis was performed at a Women’s Hospital IVF centre of 1015 female patients undergoing fresh non-donor IVF cycles. The effects of the following six single nucleotide polymorphisms (SNPs) in five IL genes on IVF outcomes were explored: IL-1α (rs1800587 C/T), IL-3 (rs40401 C/T), IL-6 (rs1800795 C/G), IL-15 (rs3806798 A/T), IL-18 (rs187238 C/G) and IL-18 (rs1946518 G/T). The main outcome measures included clinical pregnancy, embryo implantation, abortion and live birth rates. There were no statistically significant differences in clinical pregnancy, embryo implantation and live birth rates in the analysis of 1015 patients attempting their first cycle of IVF. Infertile women with IL-3 homozygous major genotype had a higher abortion rate than those with heterozygous and homozygous minor genotype (16.5% vs. 7.9%, P = 0.025). In conclusion, our results indicated that the IL-3 rs40401 polymorphism is associated with increased risk of abortion of IVF patients. Future studies with inclusion of other ethnic populations must be conducted to confirm the findings of this study. Full article
(This article belongs to the Special Issue Big Data, Decision Models, and Public Health)
Int. J. Environ. Res. Public Health EISSN 1660-4601 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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