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AI Biotech/Diagnostics: Cardio
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Patent US10176163
Issued 2019-01-08
Diagnosing Autism Spectrum Disorder Using Natural Language Processing
Embodiments herein include a natural language computing system that provides a diagnosis for a participant in the conversation which indicates the likelihood that the participant exhibited a symptom of autism. To provide the diagnosis, the computing system includes a diagnosis system that performs a training process to generate a machine learning model which is then used to evaluate a textual representation of the conversation. For example, the diagnosis system may receive one or more examples of baseline conversations that exhibit symptoms of autisms and those that do not. The diagnosis system may annotate and the baseline conversations and identify features that are used to identify the symptoms of autism. The system generates a machine learning model that weights the features according to whether the identified features are, or are not, an indicator of autism.
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- 1. A system, comprising:
a computer processor; and a memory containing a program that, when executed on the computer processor, performs an operation for processing data, comprising:
generating a machine learning (ML) model using training data comprising a first plurality of training examples, each example being a text of a conversation labeled as exhibiting at least one characteristic of autism;
receiving text of an ongoing conversation between a plurality of participants;
annotating the text of the conversation using natural language processing;
identifying features in the conversation using the annotations;
evaluating the features using the ML model to determine a measure of probability that a first one of the plurality of participants in the conversation falls on the autism spectrum; and
based on the measure of probability, outputting for display, during the conversation, a notice indicating that the first participant has exhibited a characteristic of autism.
- 7. A computer program product for diagnosing autism, the computer program product comprising:
a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executable by one or more computer processors to:
generate a ML model using training data comprising a first plurality of training examples, each example being a text of a conversation labeled as exhibiting at least one characteristic of autism;
receive text of an ongoing conversation between a plurality of participants;
annotate the text of the conversation using natural language processing;
identify features in the conversation using the annotations;
evaluate the features using the ML model to determine a measure of probability that a first one of the plurality of participants in the conversation falls on the autism spectrum; and
based on the measure of probability, output for display, during the conversation, a notice indicating that the first participant has exhibited a characteristic of autism.
