ArticleJournal of medical systems2013
Latent treatment pattern discovery for clinical processes.
Article in Journal of medical systems, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed.
- Temporal topic model for clinical pathway mining from electronic medical records.BMC medical informatics and decision making · 2024Article
- A Discrete Mathematics Approach for Understanding Risk Factors in Overactive Bladder Treatment.Cureus · 2024Article
- SDTM: A Novel Topic Model Framework for Syndrome Differentiation in Traditional Chinese Medicine.Journal of healthcare engineering · 2022Article
- Evaluation of clustering and topic modeling methods over health-related tweets and emails.Artificial intelligence in medicine · 2021Article
- Modified Needleman-Wunsch algorithm for clinical pathway clustering.Journal of biomedical informatics · 2021Article
- Patient Triage by Topic Modeling of Referral Letters: Feasibility Study.JMIR medical informatics · 2020Article
- Utilizing Electronic Medical Records to Discover Changing Trends of Medical Behaviors Over Time.Methods of information in medicine · 2017Article
- Incorporating Topic Assignment Constraint and Topic Correlation Limitation into Clinical Goal Discovering for Clinical Pathway Mining.Journal of healthcare engineering · 2017Article
- Mining Health Social Media with Sentiment Analysis.Journal of medical systems · 2016Article
- Outcome Prediction in Clinical Treatment Processes.Journal of medical systems · 2016Article
- Latent Patient Cluster Discovery for Robust Future Forecasting and New-Patient Generalization.PloS one · 2016Article
- Online treatment compliance checking for clinical pathways.Journal of medical systems · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A clinical process is typically a mixture of various latent treatment patterns, implicitly indicating the likelihood of what clinical activities are essential/critical to the process. Discovering these hidden patterns is one of the most important components of clinical process analysis. What makes the pattern discovery problem complex is that these patterns are hidden in clinical processes, are composed of variable clinical activities, and often vary significantly between patient individuals. This paper employs Latent Dirichlet Allocation (LDA) to discover treatment patterns as a probabilistic combination of clinical activities. The probability distribution derived from LDA surmises the essential features of treatment patterns, and clinical processes can be accurately described by combining different classes of distributions. The presented approach has been implemented and evaluated via real-world data sets.
Indexed as
Identifiers
23389419What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.