A wearable accessory for delivery of personalized audio service includes a first microphone for capturing sound, a first speaker for playing media, a logic circuit for creating a personalized Head Related Transfer Function (HRTF) to enhance listening experience of the media, a communication module for accessing the Internet and to provide access to the media in response to capturing the sound, and a memory storage unit for storing information related to the captured sound. Other embodiments are disclosed.

Improved approaches for media listening amongst different users are disclosed. For example, methods, systems or computer program code can enable users to have a remote listening experience in real time. Advantageously, a remote user at a remote client device can in effect listen to a particular digital media asset that is being played at a local client device of a local user. Media information and/or user profiles can also be provided about themselves and shared with other users.

A device receives a request to enroll in music sharing. After receiving the request, the device displays an enrollment user interface that includes concurrently displaying representations of a plurality of playlists created by a first user and privacy settings for the plurality of playlists. The privacy settings have default values. The enrollment user interface includes a first affordance that corresponds to a first playlist of the plurality of playlists, and a second affordance that corresponds to a second playlist of the plurality of playlists. The device receives one or more user inputs changing the privacy settings from corresponding default privacy settings to user-specified privacy settings. After completing enrollment, the device provides access to the plurality of playlists of the first user to other users with a predetermined relationship to the first user based on the privacy settings for the plurality of playlists.

A method, computer program product, and computing system for automating an intake process is executed on a computing device and includes prompting a patient to provide encounter information via a virtual assistant during a pre-visit portion of a patient encounter. Encounter information is obtained from the patient in response to the prompting by the virtual assistant.

A method, computer program product, and computing system for automated clinical documentation is executed on a computing device and includes obtaining encounter information of a patient encounter. The encounter information is processed to generate an encounter transcript. At least a portion of the encounter transcript is processed to populate at least a portion of a medical record associated with the patient encounter.

A method, computer program product, and computing system for automating a follow-up process is executed on a computing device and includes prompting a patient to provide encounter information via a virtual assistant during a post-visit portion of a patient encounter. Encounter information is obtained from the patient in response to the prompting by the virtual assistant.

Systems, methods and computer program products that facilitate dynamic playlist priority in a vehicle based upon user preferences and context. According to an embodiment, a system comprises a processor that executes computer executable components stored in at least one memory, a compilation component that receives content in a vehicle, an assessment component that respectively classifies subsets of the content, a ranking component that ranks relevancy of the classified subsets of content based upon preferences and context of a user in the vehicle, a content playback component that plays the subsets of classified content based upon relevancy ranking, a prioritization component that dynamically prioritizes a first subset of the content based upon the context of the user or context of a sender of the first subset of content, wherein the first subset of content comprises extrinsic data, and an interrupt component that interrupts playback of the subsets of classified content based upon the dynamic prioritization.

Methods, systems and computer program products are provided personalizing recommendations of items with associated explanations. The example embodiments described herein use contextual bandits to personalize explainable recommendations (“recsplanations”) as treatments (“Bart”). Bart learns and predicts satisfaction (e.g., click-through rate, consumption probability) for any combination of item, explanation, and context and, through logging and contextual bandit retraining, can learn from its mistakes in an online setting.

A method for constructing a database, comprises permitting a plurality of users to enter individual-associated data bits (IDBs) into a computerized system, each of the IDBs comprising at least one personal identifier relating to the user and relationship data comprising data on one or more related individuals and the nature of relationship; and processing the entered IDBs to generate an individual-identifier data set (IDS), one for each identified individual, being either one of the users or one of the related individuals and construct a database comprising IDSs of identified individuals.

Disclosed embodiments provide a framework to allow users of a peer-to-peer music recommendation service to generate and transmit music recommendation requests to other users of the service and obtain music recommendations that are relevant to these requests. In response to receiving a request to obtain music recommendations, the service transmits the request to a set of recipients specified in the request and from which music recommendations are to be solicited. The request specifies information that is indicative of the types of music being solicited. A recommendation received from a recipient includes identifying information of a song accessible via another music service and information indicative of a type of music of the song. Any received recommendations are presented in response to the request and feedback with regard to these recommendations is collected. Based on the provided feedback, profiles of the recipients that submitted the recommendations are updated.