Abstract: A conversational agent is provided for maintaining or improving the wellbeing of a user presenting with mental health needs by the delivery of a care protocol. The conversational agent comprises: a plurality of sub-dialogue units, each configured to deliver an element of the care protocol, and an orchestrator configured to present the sub-dialogue units to the user, sequentially, wherein each sub-dialogue unit and the orchestrator comprises: a natural language understanding module configured to receive an input and/or reply and determine at least one intent and, where present, at least one slot within the input and/or reply; a dialogue planning module configured to determine an output based, at least in part, on the at least one intent and/or slot associated within the input and/or reply, and a natural language generation module configured to provide the output to the user.

Abstract: A computer-implemented method for maintaining or improving a user's state of wellbeing, the method comprising: collecting passive data from the user; identifying a cognitive marker within the data and determining a score for the identified marker; predicting the user's state of wellbeing by inputting the score into a statistical predictive model; and generating an output configured to maintain or improve the user's state of wellbeing, wherein the output is based on the user's predicted state of wellbeing.

Abstract: A computer-implemented method for generating an acknowledgement in an automated conversational healthcare pipeline, the method comprising: receiving an input from a user; deciding whether to provide a generated acknowledgement to the user in response to the input using a filtering mechanism configured to avoid inappropriate acknowledgements; responsive to a decision to provide the generated acknowledgement, outputting the generated acknowledgement produced by processing the input using a generative acknowledgement model; and continuing with the automated healthcare pipeline, by generating a next output of the conversational healthcare pipeline and outputting the next output of the conversational healthcare pipeline.

Abstract: A computer-implemented method is provided for taking one or more action relating to therapy. The method comprising: receiving text data relating to a therapy session between a therapist and a patient; dividing the text data into a plurality of utterances; assigning a semantic representation to each of the plurality of utterances to produce a plurality of assigned utterances; aggregating the plurality of assigned utterances to form a representation of the therapy session; providing an output prediction, based on the representation of the therapy session and optionally one or more further input, of one or more characteristic of at least one of the patient, the therapist and the therapy; taking one or more action relating to the therapy, wherein the one or more action is selected based on the output prediction meeting a predetermined criterion.

Abstract: A conversational agent is provided for maintaining or improving the wellbeing of a user presenting with diabetes and mental health needs by the delivery of a care protocol. The conversational agent comprises: a plurality of sub-dialogue units, each configured to deliver an element of the care protocol, and an orchestrator configured to present the sub-dialogue units to the user, sequentially, wherein each sub-dialogue unit and the orchestrator comprises: a natural language understanding module configured to receive an input and/or reply and determine at least one intent and, where present, at least one slot within the input and/or reply: a dialogue planning module configured to determine an output based, at least in part, on the at least one intent and/or slot associated within the input and/or reply, and a natural language generation module configured to provide the output to the user.

Abstract: A conversational agent is provided for maintaining or improving the wellbeing of a user presenting with mental health needs by the delivery of a care protocol. The conversational agent comprises: a plurality of sub-dialogue units, each configured to deliver an element of the care protocol, and an orchestrator configured to present the sub-dialogue units to the user, sequentially, wherein each sub-dialogue unit and the orchestrator comprises: a natural language understanding module configured to receive an input and/or reply and determine at least one intent and, where present, at least one slot within the input and/or reply; a dialogue planning module configured to determine an output based, at least in part, on the at least one intent and/or slot associated within the input and/or reply, and a natural language generation module configured to provide the output to the user.

Abstract: 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 pre

Abstract: 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 pre

Abstract: A computer-implemented method is provided for taking one or more action relating to therapy. The method comprising: receiving text data relating to a therapy session between a therapist and a patient; dividing the text data into a plurality of utterances; assigning a semantic representation to each of the plurality of utterances to produce a plurality of assigned utterances; aggregating the plurality of assigned utterances to form a representation of the therapy session; providing an output prediction, based on the representation of the therapy session and optionally one or more further input, of one or more characteristic of at least one of the patient, the therapist and the therapy; taking one or more action relating to the therapy, wherein the one or more action is selected based on the output prediction meeting a predetermined criterion.