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A Probabilistic Reasoning Method for Predicting the Progression of Clinical Findings from Electronic Medical Records.

Goodwin T, Harabagiu SM - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: In this paper, we present a probabilistic reasoning method capable of generating predictions of the progression of clinical findings (CFs) reported in the narrative portion of electronic medical records.This method benefits from a probabilistic knowledge representation made possible by a graphical model.The knowledge encoded in the graphical model considers not only the CFs extracted from the clinical narratives, but also their chronological ordering (CO) made possible by a temporal inference technique described in this paper.

View Article: PubMed Central - PubMed

Affiliation: University of Texas at Dallas, Richardson, TX, USA.

ABSTRACT
In this paper, we present a probabilistic reasoning method capable of generating predictions of the progression of clinical findings (CFs) reported in the narrative portion of electronic medical records. This method benefits from a probabilistic knowledge representation made possible by a graphical model. The knowledge encoded in the graphical model considers not only the CFs extracted from the clinical narratives, but also their chronological ordering (CO) made possible by a temporal inference technique described in this paper. Our experiments indicate that the predictions about the progression of CFs achieve high performance given the COs induced from patient records.

No MeSH data available.


Related in: MedlinePlus

Chronological ordering (CO) of clinical findings (CFs) for a patient.
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f1-2092386: Chronological ordering (CO) of clinical findings (CFs) for a patient.

Mentions: Based on these assumptions, we automatically inferred the CO of the CFs for each patient. Figure 1 illustrates the temporal inference for one patient documented in the dataset and the resulting CO of CFs induced for that patient.


A Probabilistic Reasoning Method for Predicting the Progression of Clinical Findings from Electronic Medical Records.

Goodwin T, Harabagiu SM - AMIA Jt Summits Transl Sci Proc (2015)

Chronological ordering (CO) of clinical findings (CFs) for a patient.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525214&req=5

f1-2092386: Chronological ordering (CO) of clinical findings (CFs) for a patient.
Mentions: Based on these assumptions, we automatically inferred the CO of the CFs for each patient. Figure 1 illustrates the temporal inference for one patient documented in the dataset and the resulting CO of CFs induced for that patient.

Bottom Line: In this paper, we present a probabilistic reasoning method capable of generating predictions of the progression of clinical findings (CFs) reported in the narrative portion of electronic medical records.This method benefits from a probabilistic knowledge representation made possible by a graphical model.The knowledge encoded in the graphical model considers not only the CFs extracted from the clinical narratives, but also their chronological ordering (CO) made possible by a temporal inference technique described in this paper.

View Article: PubMed Central - PubMed

Affiliation: University of Texas at Dallas, Richardson, TX, USA.

ABSTRACT
In this paper, we present a probabilistic reasoning method capable of generating predictions of the progression of clinical findings (CFs) reported in the narrative portion of electronic medical records. This method benefits from a probabilistic knowledge representation made possible by a graphical model. The knowledge encoded in the graphical model considers not only the CFs extracted from the clinical narratives, but also their chronological ordering (CO) made possible by a temporal inference technique described in this paper. Our experiments indicate that the predictions about the progression of CFs achieve high performance given the COs induced from patient records.

No MeSH data available.


Related in: MedlinePlus