Abstract: An apparatus and method are provided for varying air flow into a specific rack space from the cold aisle, and to provide an indication of air quality. A blanking panel for a rack space includes rotatable blades that may be positioned in varying states between open and closed to vary the area through which air may flow and, thereby, vary the airflow itself. The blades may be constructed of a material that, when moisture or contaminants are present in the airflow, will indicate the presence by a change in the condition of the material.

Abstract: A method and system are described that receives enhanced cache data associated with operation of a device within a geofence, the enhanced cache data comprising Wi-Fi signal information and an entry count of a power-optimized mode being triggered within the geofence. The enhanced cache data is analyzed to identify the geofence as qualified for Wi-Fi-based triggering based on the entry count exceeding a first threshold. When the geofence is qualified, one or more candidate service set identifiers (SSIDs) are identified based on detection frequency of the one or more candidate SSIDs exceeding a second threshold. A notification is sent to a user device that presents the one or more candidate SSIDs. A selection is received from the user device of at least one SSID from the one or more candidate SSIDs, and the device is configured to use the at least one selected SSID to trigger a geofence event.

Abstract: Techniques are described that facilitate integrating artificial intelligence (AI) informatics in healthcare systems using a distributed learning platform. In one embodiment, a computer-implemented is provided that comprises interfacing, by a system operatively coupled to a processor, with a medical imaging application that provides for viewing medical image data. The method further comprises, facilitating, by the system, generation of structured diagnostic data according to a defined ontology in association with usage of the imaging application to perform a clinical evaluation of the medical image data. The method further comprises providing, by the system, the structured diagnostic data to one or more machine learning systems, wherein based on the providing, the one or more machine learning systems employ the structured diagnostic data as training data to generate or train one or more diagnostic models configured to provide artificial intelligence-based diagnostic evaluations of new medical image data.

Abstract: Techniques are described that facilitate integrating artificial intelligence (AI) informatics in healthcare systems using a distributed learning platform. In one embodiment, a computer-implemented is provided that comprises interfacing, by a system operatively coupled to a processor, with a medical imaging application that provides for viewing medical image data. The method further comprises, facilitating, by the system, generation of structured diagnostic data according to a defined ontology in association with usage of the imaging application to perform a clinical evaluation of the medical image data. The method further comprises providing, by the system, the structured diagnostic data to one or more machine learning systems, wherein based on the providing, the one or more machine learning systems employ the structured diagnostic data as training data to generate or train one or more diagnostic models configured to provide artificial intelligence-based diagnostic evaluations of new medical image data.

Abstract: Techniques are described that facilitate integrating artificial intelligence (AI) informatics in healthcare systems using a distributed learning platform. In one embodiment, a computer-implemented is provided that comprises interfacing, by a system operatively coupled to a processor, with a medical imaging application that provides for viewing medical image data. The method further comprises, facilitating, by the system, generation of structured diagnostic data according to a defined ontology in association with usage of the imaging application to perform a clinical evaluation of the medical image data. The method further comprises providing, by the system, the structured diagnostic data to one or more machine learning systems, wherein based on the providing, the one or more machine learning systems employ the structured diagnostic data as training data to generate or train one or more diagnostic models configured to provide artificial intelligence-based diagnostic evaluations of new medical image data.

Abstract: Techniques are described that facilitate integrating artificial intelligence (AI) informatics in healthcare systems using a distributed learning platform. In one embodiment, a computer-implemented is provided that comprises interfacing, by a system operatively coupled to a processor, with a medical imaging application that provides for viewing medical image data. The method further comprises, facilitating, by the system, generation of structured diagnostic data according to a defined ontology in association with usage of the imaging application to perform a clinical evaluation of the medical image data. The method further comprises providing, by the system, the structured diagnostic data to one or more machine learning systems, wherein based on the providing, the one or more machine learning systems employ the structured diagnostic data as training data to generate or train one or more diagnostic models configured to provide artificial intelligence-based diagnostic evaluations of new medical image data.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing a single point of interaction for communicating with a first agent and a second agent. An embodiment operates by a server sending a preliminary request for a preliminary response to the first agent and the second agent and, based on the preliminary request, receiving the preliminary response from the first agent. Thereafter, the server determines that the first agent is a preferred agent based on the preliminary response and maintains a line of communication to the preferred agent. The server then sends a follow-up request for a follow-up response different from the preliminary request to the preferred agent over the line of communication and receives the follow-up response from the preferred agent over the line of communication.

Abstract: Techniques are described that facilitate integrating artificial intelligence (AI) informatics in healthcare systems using a distributed learning platform. In one embodiment, a computer-implemented is provided that comprises interfacing, by a system operatively coupled to a processor, with a medical imaging application that provides for viewing medical image data. The method further comprises, facilitating, by the system, generation of structured diagnostic data according to a defined ontology in association with usage of the imaging application to perform a clinical evaluation of the medical image data. The method further comprises providing, by the system, the structured diagnostic data to one or more machine learning systems, wherein based on the providing, the one or more machine learning systems employ the structured diagnostic data as training data to generate or train one or more diagnostic models configured to provide artificial intelligence-based diagnostic evaluations of new medical image data.

Abstract: Techniques are described that facilitate integrating artificial intelligence (AI) informatics in healthcare systems using a distributed learning platform. In one embodiment, a computer-implemented is provided that comprises interfacing, by a system operatively coupled to a processor, with a medical imaging application that provides for viewing medical image data. The method further comprises, facilitating, by the system, generation of structured diagnostic data according to a defined ontology in association with usage of the imaging application to perform a clinical evaluation of the medical image data. The method further comprises providing, by the system, the structured diagnostic data to one or more machine learning systems, wherein based on the providing, the one or more machine learning systems employ the structured diagnostic data as training data to generate or train one or more diagnostic models configured to provide artificial intelligence-based diagnostic evaluations of new medical image data.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing a single point of interaction for communicating with a first agent and a second agent. An embodiment operates by a server sending a preliminary request for a preliminary response to the first agent and the second agent and, based on the preliminary request, receiving the preliminary response from the first agent. Thereafter, the server determines that the first agent is a preferred agent based on the preliminary response and maintains a line of communication to the preferred agent. The server then sends a follow-up request for a follow-up response different from the preliminary request to the preferred agent over the line of communication and receives the follow-up response from the preferred agent over the line of communication.

Abstract: Provided are methods and compositions for treating cancer using an effective amount of a PD-1 antagonist (e.g., an antibody) in combination with a TIM-4 antagonist (e.g., an antibody).

Abstract: A device may receive a request for imaging of a particular location. The device may identify one or more sensors associated with imaging the particular location. The device may select a sensor, of the one or more sensors, for imaging the particular location. The sensor may be associated with an autonomous vehicle. The device may cause the autonomous vehicle to move the sensor to the particular location. The device may receive imaging of the particular location based on causing the autonomous vehicle to move the sensor to the particular location. The device may selectively combine the imaging of the particular location with archived other imaging of the particular location. The device may provide imaging of the particular location to fulfill the request for imaging of the particular location based on selectively combining the imaging of the particular location with archived imaging of the particular location.

Abstract: A device may receive a request for imaging of a particular location. The device may identify one or more sensors associated with imaging the particular location. The device may select a sensor, of the one or more sensors, for imaging the particular location. The sensor may be associated with an autonomous vehicle. The device may cause the autonomous vehicle to move the sensor to the particular location. The device may receive imaging of the particular location based on causing the autonomous vehicle to move the sensor to the particular location. The device may selectively combine the imaging of the particular location with archived other imaging of the particular location. The device may provide imaging of the particular location to fulfill the request for imaging of the particular location based on selectively combining the imaging of the particular location with archived imaging of the particular location.

Abstract: A temporary, disposable shoe cover for bowling includes an upper, a sole having a first sole portion and a second sole portion, and a retainer. The upper is made of a fabric. A bottom opening of the upper is attached to a perimeter of the sole. A top opening of the upper is adapted to receive the user's shoe and/or foot. The retainer is attached to (i.e., at or near) the top opening of the upper and is operable to retain the shoe cover on the user's shoe and/or foot. The first sole portion is on an anterior portion of the sole and made of a low friction fabric (e.g., felt, cotton, or a nonwoven fabric). The second sole portion is on a posterior portion of the sole and made of a high friction fabric (e.g., rubber, rubber impregnated cotton, or flannel backed cotton with nonskid vinyl or rubber dots).

Abstract: Methods for treating patients with cancer and autoimmune disorders using IL-28 and IL-29 molecules. The IL-28 and IL-29 molecules include polypeptides that have homology to the human IL-28 or IL-29 polypeptide sequence and proteins fused to a polypeptide with IL-28 and IL-29 functional activity. The molecules can be used as a monotherapy or in combination with other known cancer and/or autoimmune therapeutics.

Abstract: Methods for treating patients with cancer and autoimmune disorders using IL-28 and IL-29 molecules. The IL-28 and IL-29 molecules include polypeptides that have homology to the human IL-28 or IL-29 polypeptide sequence and proteins fused to a polypeptide with IL-28 and IL-29 functional activity. The molecules can be used as a monotherapy or in combination with other known cancer and/or autoimmune therapeutics.

Abstract: Methods for treating patients with cancer and autoimmune disorders using IL-28 and IL-29 molecules. The IL-28 and IL-29 molecules include polypeptides that have homology to the human IL-28 or IL-29 polypeptide sequence and proteins fused to a polypeptide with IL-28 and IL-29 functional activity. The molecules can be used as a monotherapy or in combination with other known cancer and/or autoimmune therapeutics.

Abstract: A system and methods for organizing, manipulating, and displaying worklists of patient studies for access by medical personnel is provided. The patient studies may include medical images and data relating to medical images. In some embodiments, the worklists are easily customizable, to permit a wide range of tasks to be handled in the worklist system. Updated worklist information may be pushed to the appropriate workstations or users in nearly real-time, as updates become available, reducing errors that may be caused by outdated information in worklists. In some embodiments, worklists contain overlapping information, which permits numerous users to see the information, even if it is not immediately relevant to their tasks. This increased scrutiny may help to reduce errors.

Abstract: The subject mater herein relates to voice applications and, more particularly, speech recognition application grammar modeling. Various embodiments provide systems, methods, and software to present one or more user interfaces through which to receive input to define and manipulate properties of a graphical listen element, wherein the properties identify one or more data sources. Some such embodiments further include building a speech recognition program grammar as a function of one or more graphical listen elements, wherein the grammar includes a representation of data retrieved from the one or more data sources.

Abstract: Systems, methods, and computer program products for determining voice recognition accuracy of a voice recognition system are provided. In one embodiment, voice recognition information produced by a voice recognition system in response to recognizing a user utterance is analyzed. The voice recognition information comprises a recognized voice command associated with the user utterance and a reference to an audio file that includes the user utterance. Based on the analysis, a recognition error may be identified and the source of the error determined. A solution is then automatically implemented to eliminate the source of the error. As part of the analysis, the user utterance may be transcribed to create a transcribed utterance, if the recognized voice command does not match the user utterance. The transcribed utterance may then be compared to the recognized voice command to identify an error.