Editor's Choice Series for Medical Statistics and Data Science Section

A special issue of BioMedInformatics (ISSN 2673-7426). This special issue belongs to the section "Medical Statistics and Data Science".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 1633

Special Issue Editor


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Guest Editor
Medical Informatics and Data Analysis Research Group, University of Oulu, P.O. Box 5000, FI-90014 Oulu, Finland
Interests: medical statistics; data informatics; statistics in medical journals; statistical computing; statistical modelling; data presentation; bibliometrics; information retrieval
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Special Issue Information

Dear Colleagues,

The Editor's Choice Series for Medical Statistics and Data Science Section presents a curated compilation focusing on advanced statistical methodologies and data science applications within the medical domain. This series highlights innovative approaches, analytical tools, and methodologies shaping the landscape of medical research, clinical trials, and healthcare decision making.

Encompassing diverse areas such as biostatistics, epidemiology, clinical trial design, predictive modeling, and data-driven healthcare, this series delves into the techniques enhancing evidence-based medicine and driving advancements in healthcare practices. Moving from robust statistical frameworks for clinical studies to predictive analytics aiding personalized healthcare, these articles elucidate the pivotal role of statistics and data science in medical advancements.

Please note that this series does not consider brief reports for publication, emphasizing comprehensive studies, methodological analyses, and practical applications within medical statistics and data science.

Dr. Pentti Nieminen
Guest Editor

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 submissions that pass pre-check are 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. BioMedInformatics is an international peer-reviewed open access quarterly 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 1000 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

  • biostatistics
  • epidemiology
  • clinical trials
  • predictive modeling
  • data-driven healthcare
  • evidence-based medicine
  • statistical frameworks
  • medical research
  • healthcare decision-making
  • statistical reporting
  • health sciences
  • dentistry

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Published Papers (1 paper)

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Research

10 pages, 926 KiB  
Article
Cross-National Analysis of Opioid Prescribing Patterns: Enhancements and Insights from the OralOpioids R Package in Canada and the United States
by Ankona Banerjee, Kenneth Nobleza, Duc T. Nguyen and Erik Stricker
BioMedInformatics 2024, 4(3), 2107-2116; https://doi.org/10.3390/biomedinformatics4030112 - 16 Sep 2024
Viewed by 1169
Abstract
Background: The opioid crisis remains a significant public health challenge in North America, highlighted by the substantial need for tools to analyze and understand opioid potency and prescription patterns. Methods: The OralOpioids package automates the retrieval, processing, and analysis of opioid data from [...] Read more.
Background: The opioid crisis remains a significant public health challenge in North America, highlighted by the substantial need for tools to analyze and understand opioid potency and prescription patterns. Methods: The OralOpioids package automates the retrieval, processing, and analysis of opioid data from Health Canada’s Drug Product Database (DPD) and the U.S. Food and Drug Administration’s (FDA) National Drug Code (NDC) database. It includes functions such as load_Opioid_Table, which integrates country-specific data processing and Morphine Equivalent Dose (MED) calculations, providing a comprehensive dataset for analysis. The package facilitates a comprehensive examination of opioid prescriptions, allowing researchers to identify high-risk opioids and patterns that could inform policy and healthcare practices. Results: The integration of MED calculations with Canadian and U.S. data provides a robust tool for assessing opioid potency and prescribing practices. The OralOpioids R package is an essential tool for public health researchers, enabling a detailed analysis of North American opioid prescriptions. Conclusions: By providing easy access to opioid potency data and supporting cross-national studies, the package plays a critical role in addressing the opioid crisis. It suggests a model for similar tools that could be adapted for global use, enhancing our capacity to manage and mitigate opioid misuse effectively. Full article
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