The methods and systems may improve the development of protocol documents used for clinical trials. The methods and systems may automatically estimate the likelihood of success or failure of executing a protocol document for a clinical study using a machine learning model that leverages several hundred thousand of past protocol documents and the outcomes of the clinical studies. The methods and systems may highlight sections of the protocol document that may increase a likelihood of an unsuccessful execution of the protocol document and may provide one or more recommendations to improve the highlighted sections of the protocol document.

The methods and systems may improve the development of protocol documents used for clinical trials. The methods and systems may automatically estimate the likelihood of success or failure of executing a protocol document for a clinical study using a machine learning model that leverages several hundred thousand of past protocol documents and the outcomes of the clinical studies. The methods and systems may highlight sections of the protocol document that may increase a likelihood of an unsuccessful execution of the protocol document and may provide one or more recommendations to improve the highlighted sections of the protocol document.

Systems and methods for automated local story generation and curation are described. In one example embodiment, a server computer receives content from client devices, and processes the content to identify content characteristics. Stories are then generated based on the characteristics of the received content, and the stories are communicated to client devices. In certain embodiments, selection at a client device of an individual piece of content within a story may further be used by the system to provide the client device with a sub-story that includes pieces of content sharing content characteristics with the characteristics of the selected image or video.

Systems and methods for automated local story generation and curation are described. In one example embodiment, a server computer receives content from client devices, and processes the content to identify content characteristics. Stories are then generated based on the characteristics of the received content, and the stories are communicated to client devices. In certain embodiments, selection at a client device of an individual piece of content within a story may further be used by the system to provide the client device with a sub-story that includes pieces of content sharing content characteristics with the characteristics of the selected image or video.

Chat-based interaction with an in-meeting virtual assistant may be provided. First, audio input associated with a meeting may be received. Next, an intent from the audio input may be detected. Text content associated with the audio input may then be generated in response to detecting the intent from the audio input. The text content may be displayed in a chat interface.

A device may receive access information that permits access to messages associated with an electronic messaging account. The device may process the messages associated with the electronic messaging account to identify one or more of the messages that include at least one coupon after receiving the access information. The one or more of the messages may be identified using at least two of an image processing technique, a text processing technique, or a code processing technique. The device may store information identifying the one or more of the messages that include the at least one coupon after processing the messages. The device may perform one or more actions to facilitate use of the at least one coupon in association with completing a transaction.

A device may receive access information that permits access to messages associated with an electronic messaging account. The device may process the messages associated with the electronic messaging account to identify one or more of the messages that include at least one coupon after receiving the access information. The one or more of the messages may be identified using at least two of an image processing technique, a text processing technique, or a code processing technique. The device may store information identifying the one or more of the messages that include the at least one coupon after processing the messages. The device may perform one or more actions to facilitate use of the at least one coupon in association with completing a transaction.

A computer implemented method for managing medical information includes displaying a number of user interface elements within a graphical user interface, receiving medical information for a patient in a first user interface element of the user interface elements, processing the medical information to identify one or more semantic items, the one or more semantic items including a first semantic item, processing a medical record for the patient according to first semantic item, the processing including identifying a number of medical information items related to the first semantic item, and presenting at least some medical information items of the number of medical information items in a second user interface element configured to display medical information items related to the first semantic item.

A computer implemented method for managing medical information includes displaying a number of user interface elements within a graphical user interface, receiving medical information for a patient in a first user interface element of the user interface elements, processing the medical information to identify one or more semantic items, the one or more semantic items including a first semantic item, processing a medical record for the patient according to first semantic item, the processing including identifying a number of medical information items related to the first semantic item, and presenting at least some medical information items of the number of medical information items in a second user interface element configured to display medical information items related to the first semantic item.

A multicore apparatus determines fitness of a candidate for a role. The apparatus includes a multicore system processing device, a plurality of parallel multicore graphics processing devices, a network interface device, a storage device, and a system interface bus. The network interface device provides remote connection to the multicore system processing device. The storage device stores training data including positive and negative examples. The positive examples represent candidates who would be invited to an interview, and the negative examples represent candidates who would not be invited to an interview. The positive and negative examples are used by the plurality of parallel multicore graphics processing devices to train a deep learning model, which is used by the multicore system processing device to determine fitness of the candidate for the role while eliminating unwanted bias.