Abstract: A method and system is provided for assisting a user to assign a label to words or spans of text in a transcript of a conversation between a patient and a medical professional and form groupings of such labelled words or spans of text in the transcript. The transcript is displayed on an interface of a workstation. A tool is provided for highlighting spans of text in the transcript consisting of one or more words. Another tool is provided for assigning a label to the highlighted spans of text. This tool includes a feature enabling searching through a set of predefined labels available for assignment to the highlighted span of text. The predefined labels encode medical entities and attributes of the medical entities. The interface further includes a tool for creating groupings of related highlighted spans of texts. The tools can consist of mouse action or key strokes or a combination thereof.

Abstract: A method and workstation for generating a transcript of a conversation between a patient and a healthcare practitioner is disclosed. A workstation is provided with a tool for rendering of an audio recording of the conversation and generating a display of a transcript of the audio recording using a speech-to-text engine, thereby enabling inspection of the accuracy of conversion of speech to text. A tool is provided for scrolling through the transcript and rendering the portion of the audio according to the position of the scrolling. There is a highlighting in the transcript of words or phrases spoken by the patient relating to symptoms, medications or other medically relevant concepts. Additionally, there is provided a set of transcript supplement tools enabling editing of specific portions of the transcript based on the content of the corresponding portion of audio recording.

Abstract: A method for automatically generating a note summarizing a conversation between a patient and a healthcare provider is disclosed. A workstation is provided with a tool for rendering an audio recording of the conversation and a display for displaying a transcript of the audio recording obtained from a speech-to-text engine. The display of the workstation includes first transcript region for display of the transcript and a second note region for simultaneous displaying of elements of a note summarizing the conversation. Words or phrases in the transcript related to medical topics relating to the patient are extracted with the aid of a trained machine learning model. The extracted words or phrases are highlighted in the transcript and displayed in the note region.

Abstract: In one aspect, an example method involves selecting, by a computing device, a message to be output to a user; determining a classification group to which the user belongs; using the determined classification group to which the user belongs as a basis to select a device from among a plurality of devices associated with the user; and transmitting, by the computing device, an instruction via a communication network, wherein the instruction is configured to cause the selected device to output the selected message.

Abstract: Methods and systems for improving a presentation function of a client device based on feedback data indicative of presentation effectiveness are disclosed. A server transmits, over a communication network, a first instruction that configures the client device to provide a first presentation via a user interface to an individual. The server receives physiological data collected by one or more sensors of the client device and associated with the individual and the first presentation. Based on feedback data, including the received physiological data, representative of behavior change subject to the first presentation, the server computes an effectiveness assessment of the first presentation.

Abstract: Systems and methods of predicting documentation associated with an encounter between attendees are provided. For instance, attendee data indicative of one or more previous visit notes associated with a first attendee can be obtained. The attendee data can be inputted into a machine-learned note prediction model that includes a neural network. The neural network can generate one or more context vectors descriptive of the attendee data. Data indicative of a predicted visit note can be received as output of the machine-learned note prediction model based at least in part on the context vectors. The predicted visit note can include a set of predicted information expected to be included in a subsequently generated visit note associated with the first attendee.

Abstract: Some embodiments of the present disclosure provide a method that includes compiling, for each of a plurality of individuals, health-related data in a plurality of categories, determining that a given individual has a particular type of health-related data in a particular set of one or more categories, and based on the determination that the given individual has the particular type of health-related data in the particular set of one or more categories, transmitting from a server device to a client device associated with the given individual, over a communication network, a first instruction configured to cause the client device to present a first incentive designed to cause a change in the given individual's health-related data. The first incentive may make use of a first type of motivational foundation. The method may also include determining whether the first incentive was effective or ineffective.