Call for content!
Real-world data and evidence become increasingly important in medical science and health care. The effort in curbing the COVID-19 pandemic is a perfect example of that. Real-world health data and evidence may come from different sources such as computers, mobile devices, and wearables and have various types such as internet searches, social media, electronic health/medical records. The vast amount and different types of real-world data and evidence hold great potential for new scientific discovery and solving problems and making decisions that are otherwise infeasible. Meanwhile, new, effective, and practically feasible statistical and machine learning methods are needed to unlock the potential in the real-world data so practitioners and decision makers can apply the results and conclusions to better meet the medical and healthcare needs of our society.
In this BMC Medical Research Methodology collection, we look for articles and contributions on the following topics:
- Statistical and machine learning methods for real-world data analysis, which include but are not limited to internet traffic and searches, social media data, mobile device, wearable and apps data, electronic health/medical records, claims and billing activities.
- New applications of existing methods to real-world data sets that are scientifically and practically relevant.
- New and useful real-world data and evaluation of important data sources.
- Review and comparisons of existing methods for real-world studies/data and evidence, identification of opportunities and challenges in research direction.
- Causality and real-world data; how close are we?
- Big Data challenges in medical research
This collection welcomes submissions of Research articles, Database articles and Software articles. Unsolicited narrative reviews will not be considered, as per the journal's policies.
Datasets and data descriptions relevant to the collection will be considered in BMC Research Notes as Data Notes. You can find out more about this article type here. This type of content will be published in BMC Research Notes and included in the final collection.
Articles will undergo the journal’s standard peer-review process overseen by our Guest Editors, Prof. Demosthenes Panagiotakos (Harokopio University, Greece) and Prof. Fang Liu (University of Notre Dame, USA).
Before submitting your manuscript, please ensure you have carefully read the submission guidelines for BMC Medical Research Methodology. Please ensure you highlight in your cover letter that you are submitting to a collection and select the collection in the submission questionnaire in Editorial Manager.
Submission deadline: 31 October 2022