Learning Or Inferring Medical Concepts From Medical Transcripts
First Claim
1. A system for inferring a medical concept from a medical transcript, the system comprising:
- an input operable to receive user identification of the medical transcript;
a processor operable to receive a text passage from the medical transcript and operable to apply a probabilistic model to the text passage of the medical transcript, the probabilistic model trained as a function of a discrete set of words or phrases; and
a display operable to output a state associated with a patient, the state being inferred as a function of an output from the probabilistic model applied to the text passage.
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Abstract
A medical concept is learned about or inferred from a medical transcript. A probabilistic model is trained from medical transcripts. For example, the problem is treated as a graphical model. Discrimitive or generative learning is used to train the probabilistic model. A mutual information criterion can be employed to identify a discrete set of words or phrases to be used in the probabilistic model The model is based on the types of medical transcripts, focusing on this source of data to output the most probable state of a patient in the medical field or domain. The learned model may be used to infer a state of a medical concept for a patient
36 Citations
19 Claims
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1. A system for inferring a medical concept from a medical transcript, the system comprising:
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an input operable to receive user identification of the medical transcript;
a processor operable to receive a text passage from the medical transcript and operable to apply a probabilistic model to the text passage of the medical transcript, the probabilistic model trained as a function of a discrete set of words or phrases; and
a display operable to output a state associated with a patient, the state being inferred as a function of an output from the probabilistic model applied to the text passage. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 12)
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11. In a computer readable storage medium having stored therein data representing instructions executable by a programmed processor for inferring a medical concept from a medical transcript, the instructions comprising:
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applying a probabilistic model to the medical transcript of a patient, the probabilistic model probabilistically associating different words of the medical transcript to a state of the medical concept, wherein the probabilistic model comprises a Bayes model having a summary node for the text passage, a negation node, and a modifier node; and
outputting the state as indicated by the medical transcript of the medical concept as a function of the probabilistic associations of the different words to the state. - View Dependent Claims (13)
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14. A method for learning about a medical concept from a medical transcript, the method comprising:
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receiving a plurality of labeled text passages from medical transcripts;
constructing, with a processor, a probabilistic model of the medical concept as a function of the labeled text passages of the medical transcripts, the constructing being a function of discriminative learning; and
outputting the probabilistic model. - View Dependent Claims (15, 16, 17, 18, 19)
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Specification