Prognosis of Clinical Outcomes with Temporal Patterns and Experiences with One Class Feature Selection.

IEEE/ACM Trans Comput Biol Bioinform 2017 May-Jun;14(3):555-563. Epub 2016 Jul 14.

Accurate prognosis of outcome events, such as clinical procedures or disease diagnosis, is central in medicine. The emergence of longitudinal clinical data, like the Electronic Health Records (EHR), represents an opportunity to develop automated methods for predicting patient outcomes. However, these data are highly dimensional and very sparse, complicating the application of predictive modeling techniques. Further, their temporal nature is not fully exploited by current methods, and temporal abstraction was recently used which results in symbolic time intervals representation. We present Maitreya, a framework for the prediction of outcome events that leverages these symbolic time intervals. Using Maitreya, learn predictive models based on the temporal patterns in the clinical records that are prognostic markers and use these markers to train predictive models for eight clinical procedures. In order to decrease the number of patterns that are used as features, we propose the use of three one class feature selection methods. We evaluate the performance of Maitreya under several parameter settings, including the one-class feature selection, and compare our results to that of atemporal approaches. In general, we found that the use of temporal patterns outperformed the atemporal methods, when representing the number of pattern occurrences.

Download full-text PDF

Source
http://dx.doi.org/10.1109/TCBB.2016.2591539DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5486920PMC
November 2017
10 Reads

Publication Analysis

Top Keywords

temporal patterns
12
feature selection
12
class feature
8
symbolic time
8
outcome events
8
predictive models
8
clinical procedures
8
time intervals
8
temporal
5
maitreya learn
4
intervals maitreya
4
leverages symbolic
4
events leverages
4
application predictive
4
learn predictive
4
complicating application
4
records prognostic
4
prognostic markers
4
clinical records
4
patterns clinical
4

Similar Publications