Latent Treatment Pattern Discovery for Clinical Processes

Huang, Zhengxing; Lü, Xudong; Duan, Huilong

doi:10.1007/s10916-012-9915-2

Cited by 49 publications

(25 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [124] introduced an LDA based method to discover patterns of internal treatment for Clinical processes (CPs), and currently, detect these hidden patterns is one of the most serious elements of clinical process evaluation. Their main approach is to obtain care flow logs and also estimate hidden patterns for the gathered logs based on LDA.…”

Section: Topic Modeling In Medical and Biomedicalmentioning

confidence: 99%

Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey

Jelodar

Wang

Yuan

et al. 2018

Multimed Tools Appl

1,110

473

View full text Add to dashboard Cite

Topic modeling is one of the most powerful techniques in text mining for data mining, latent data discovery, and finding relationships among data and text documents. Researchers have published many articles in the field of topic modeling and applied in various fields such as software engineering, political science, medical and linguistic science, etc. There are various methods for topic modelling; Latent Dirichlet Allocation (LDA) is one of the most popular in this field. Researchers have proposed various models based on the LDA in topic modeling. According to previous work, this paper will be very useful and valuable for introducing LDA approaches in topic modeling. In this paper, we investigated highly scholarly articles (between 2003 to 2016) related to topic modeling based on LDA to discover the research development, current trends and intellectual structure of topic modeling. In addition, we summarize challenges and introduce famous tools and datasets in topic modeling based on LDA.

show abstract

Section: Topic Modeling In Medical and Biomedicalmentioning

confidence: 99%

Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey

Jelodar

Wang

Yuan

et al. 2018

Multimed Tools Appl

1,110

473

View full text Add to dashboard Cite

show abstract

“…Huang et al [2] firstly introduced LDA to extract latent topics as the treatment patterns from clinical data. Each patient trace was regarded as a mixture of different treatment patterns.…”

Section: Related Workmentioning

confidence: 99%

Incorporating Topic Assignment Constraint and Topic Correlation Limitation into Clinical Goal Discovering for Clinical Pathway Mining

Xiao

Jin

Wei

et al. 2017

Journal of Healthcare Engineering

View full text Add to dashboard Cite

Clinical pathways are widely used around the world for providing quality medical treatment and controlling healthcare cost. However, the expert-designed clinical pathways can hardly deal with the variances among hospitals and patients. It calls for more dynamic and adaptive process, which is derived from various clinical data. Topic-based clinical pathway mining is an effective approach to discover a concise process model. Through this approach, the latent topics found by latent Dirichlet allocation (LDA) represent the clinical goals. And process mining methods are used to extract the temporal relations between these topics. However, the topic quality is usually not desirable due to the low performance of the LDA in clinical data. In this paper, we incorporate topic assignment constraint and topic correlation limitation into the LDA to enhance the ability of discovering high-quality topics. Two real-world datasets are used to evaluate the proposed method. The results show that the topics discovered by our method are with higher coherence, informativeness, and coverage than the original LDA. These quality topics are suitable to represent the clinical goals. Also, we illustrate that our method is effective in generating a comprehensive topic-based clinical pathway model.

show abstract

“…For instance, Klundert et al developed dynamic programming formulations for compliance measurement in clinical pathways [7]. In our previous work, we presented a probabilistic topic model for discovering the underlying treatment patterns from clinical event logs [3], which discloses essential features of CPs by combining different classes of distributions. The derived patterns that shared by most of the patient traces can be used as a compliance measure.…”

Section: Related Workmentioning

confidence: 99%

“…Health-care organizations seek for a better control of their medical services not only to satisfy treatment requirements but also to leverage cost-saving opportunities through standardization of treatment behaviors in clinical pathways (CPs) [1][2][3][4][5][6]. With this respect, compliance checking is important as it ensures that treatment behaviors of a healthcare organization act in accordance with the established CP specifications [7].…”

Section: Introductionmentioning

confidence: 99%

Online Treatment Compliance Checking for Clinical Pathways

et al. 2014

Self Cite

View full text Add to dashboard Cite

Compliance checking for clinical pathways (CPs) is getting increasing attention in health-care organizations due to stricter requirements for cost control and treatment excellence. Many compliance measures have been proposed for treatment behavior inspection in CPs. However, most of them look at aggregated data seen from an external perspective, e.g. length of stay, cost, infection rate, etc., which may provide only a posterior impression of the overall conformance with the established CPs such that in-depth and in near real time checking on the compliance of the essential/critical treatment behaviors of CPs is limited. CP specification and support online compliance checking, this article presents a semantic rule-based CP compliance checking system. In detail, we construct a CP ontology (CPO) model to provide a formal grounding of CP compliance checking. Using the proposed CPO, domain treatment constraints are modeled into Semantic Web Rule Language (SWRL) rules to specify the underlying treatment behaviors and their quantified temporal structure in a CP. The established SWRL rules are integrated with the CP workflow such that a series of applicable compliance checking and evaluation can be reminded and recommended during the pathway execution. The proposed approach can, therefore, provides a comprehensive compliance checking service as a paralleling activity to the patient treatment journey of a CP rather than an afterthought. The proposed approach is illustrated with a case study on the unstable angina clinical pathway implemented in the Cardiology Department of a Chinese hospital. The results demonstrate that the approach, as a feasible solution to provide near real time conformance checking of CPs, not only enables clinicians to uncover non-compliant treatment behaviors, but also empowers clinicians with the capability to make informed decisions when dealing with treatment compliance violations in the pathway execution.

show abstract

Latent Treatment Pattern Discovery for Clinical Processes

Cited by 49 publications

References 23 publications

Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey

Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey

Incorporating Topic Assignment Constraint and Topic Correlation Limitation into Clinical Goal Discovering for Clinical Pathway Mining

Online Treatment Compliance Checking for Clinical Pathways

Contact Info

Product

Resources

About