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公开(公告)号:US20200005929A1
公开(公告)日:2020-01-02
申请号:US16486467
申请日:2018-03-01
摘要: A computer-based psychotherapy triage method comprising: obtaining text data relating to a patient at an initial stage of a therapy process; using at least a first part of a deep learning model to obtain a representation of at least the text data; using at least a second part of the deep learning model, and an input thereto formed using the representation, to obtain an output predicting a characteristic of a condition of the patient and/or of the therapy process; and causing the system to take one or more actions relating to the therapy process, wherein the one or more actions are selected based on the output; wherein the deep learning model is trained using a training set comprising, for a plurality of other patients, text data relating to the other patient at an initial stage of a therapy process and a result of a determination of the characteristic.
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公开(公告)号:US11990223B2
公开(公告)日:2024-05-21
申请号:US17283837
申请日:2019-10-10
摘要: A computer-implemented method is provided for taking one or more actions relating to therapy, the method comprising: obtaining data comprising audio data relating to a therapy session between a therapist and one or more patients; extracting text data from the audio data to form a transcript; dividing the transcript into a plurality of utterances; using at least a first part of a deep learning model to assign a semantic representation to each of the plurality of utterances to produce a plurality of assigned utterances; compiling the plurality of assigned utterances to form a representation of the therapy session; using at least a second part of a deep learning model, and an input comprising the representation of the therapy session, to obtain an output predicting a characteristic of the therapist, and/or the therapy, and/or the one or more patient; and causing the system to take one or more actions relating to the therapy, wherein the one or more actions are selected based on the output meeting one or more predetermined criterion.
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