2014 UnsupervisedLearningofDiseasePr

• (Wang et al., 2014) ⇒ Xiang Wang, David Sontag, and Fei Wang. (2014). “Unsupervised Learning of Disease Progression Models.” In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) Journal. ISBN:978-1-4503-2956-9 doi:10.1145/2623330.2623754

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Cited By

• http://scholar.google.com/scholar?q=%222014%22+Unsupervised+Learning+of+Disease+Progression+Models
• http://dl.acm.org/citation.cfm?id=2623330.2623754&preflayout=flat#citedby

Quotes

Author Keywords

• Bayesian network; data mining; disease progression modeling; [[markov jump process; medical informatics

Abstract

Chronic diseases, such as Alzheimer's Disease, Diabetes, and Chronic Obstructive Pulmonary Disease, usually progress slowly over a long period of time, causing increasing burden to the patients, their families, and the healthcare system. A better understanding of their progression is instrumental in early diagnosis and personalized care. Modeling disease progression based on real-world evidence is a very challenging task due to the incompleteness and irregularity of the observations, as well as the heterogeneity of the patient conditions. In this paper, we propose a probabilistic disease progression model that address these challenges. As compared to existing disease progression models, the advantage of our model is three-fold: 1) it learns a continuous-time progression model from discrete-time observations with non-equal intervals; 2) it learns the full progression trajectory from a set of incomplete records that only cover short segments of the progression; 3) it learns a compact set of medical concepts as the bridge between the hidden progression process and the observed medical evidence, which are usually extremely sparse and noisy. We demonstrate the capabilities of our model by applying it to a real-world COPD patient cohort and deriving some interesting clinical insights.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 UnsupervisedLearningofDiseasePr	David Sontag Xiang Wang Fei Wang			Unsupervised Learning of Disease Progression Models				10.1145/2623330.2623754		2014