Temporal issues are intrinsic to the biomedical domain, due to its inherent longitudinal nature. This observation holds whether referring to Electronic Health Records (EHRs) emphasizing the slowly accumulating data in chronic-care domains such as the management of diabetes patients, or the data accumulating rapidly in fast-paced domains such as in the Intensive Care Unit (ICU), or the data collected continuously in varying forms by personal monitoring devices (e.g., smart-watches, wearable devices, etc.). Although the temporal aspect of biomedical data is well recognized as essential, and several methods for time series analysis, temporal reasoning, and temporal data mining have been developed over the past decades, there is much room for additional contributions ,  and .
The data mining ,  and  and biomedical informatics , , , , ,  and  literatures increasingly feature studies dealing with the main challenges related to analyzing the data of EHRs that include large numbers of variables, varying sampling frequencies, and different types of events, either instantaneous or having a duration. These challenges had necessitated the use of methods from multiple scientific fields, such as temporal abstraction, frequent-pattern mining, temporal regression models, hidden Markov models, and more.
In addition to enhancing the computational efficiency of the analytical methods, the investigation of such techniques in time-oriented domains promises to improve the quality of patient care through the discovery of meaningful clinical knowledge. Thus, in this call for papers, we encourage participation from researchers in all fields related to medical data research, including mainstream temporal data mining, time series processing, and more.
The topics of this special issue include, but are not limited to, the following:
Temporal Pattern Discovery
Time Intervals Mining
Streams Data Mining
Periodic Pattern Mining
Patient Behavior Analysis
Time Series Analysis
Univariate time series
Multivariate time series
Numeric and regression analysis
Symbolic and discretization based methods
Irregular temporal data analysis
Imputation for temporal data
Knowledge-based temporal reasoning
Knowledge-based temporal abstraction
Complex Events Processing
Big Data Temporal Data Mining
Parallelizing Temporal Data Mining
Prediction and Forecasting
Temporal Data Retrieval
Dynamic Time Warping
Time Series Similarity
JBI is particularly interested in publishing methodological reviews on topics relevant to special issues, and we encourage submissions of this type.
All submitted papers must be original and will go through a rigorous peer-review process with at least two reviewers. All submissions should follow the guidelines for authors available through a link on the Journal of Biomedical Informatics web site (www.journals.elsevier.com/journal-of-biomedical-informatics).
JBI’s editorial policy is also outlined on that page and will be strictly followed by special issue reviewers.
Authors must submit their papers via the online Elsevier Editorial System (EES) at http://ees.elsevier.com/jbi by November 1, 2016. Authors can register and upload their text, tables, and figures as well as subsequent revisions through this website. Potential authors may contact the Publishing Services Coordinator in the journal’s editorial office (email@example.com) for questions regarding this process. Authors are also welcome to discuss their potential submissions with the editors by sending an email to Robert Moskovitch (firstname.lastname@example.org) regarding the potential fit of their submission with this special issue.