DIAGNOSING AUTISM SPECTRUM DISORDER USING NATURAL LANGUAGE PROCESSING

摘要

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.

主权项

1. A method for evaluating a textual conversation, 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 a conversation between a plurality of participants; evaluating the text of the conversation to generate features using natural language processing; and evaluating the features using the ML model to determine a measure of probability that one of the plurality of participants falls on the autism spectrum.