Abstract: A website building system (WBS) includes a processor implementing a machine learning feedback-based proposal module and a database storing at least the web sites of a plurality of users of the WBS, and components of the websites. The module includes a plurality of per activity AI units and a feedback system. Each per activity AI unit supports one or more specific activity related to the WBS and provides at least one system suggestion to the users related to its specific activity. Each per activity AI unit includes at least one machine learning model suitable for the activity supported by its per activity AI unit. The feedback system provides a plurality of different kinds of feedback from the users and from rule engines for updating the machine learning models. The feedback system analyzes the feedback to determine which one of the at least one machine learning models to update.

Abstract: A website building system (WBS) includes a processor implementing a machine learning feedback-based proposal module and a database storing at least the websites of a plurality of users of the WBS, and components of the websites. The module includes a plurality of per activity AI units and a feedback system. Each per activity AI unit supports one or more specific activity related to the WBS and provides at least one system suggestion to the users related to its specific activity. Each per activity AI unit includes at least one machine learning model suitable for the activity supported by its per activity AI unit. The feedback system provides a plurality of different kinds of feedback from the users for updating the machine learning models. The feedback system analyzes the feedback to determine which one of the at least one machine learning models to update.

Abstract: A website building system (WBS) includes a processor implementing a machine learning feedback-based proposal module and a database storing at least the websites of a plurality of users of the WBS, and components of the websites. The module includes a plurality of per activity AI units and a feedback system. Each per activity AI unit supports one or more specific activity related to the WBS and provides at least one system suggestion to the users related to its specific activity. Each per activity AI unit includes at least one machine learning model suitable for the activity supported by its per activity AI unit. The feedback system provides a plurality of different kinds of feedback from the users for updating the machine learning models. The feedback system analyzes the feedback to determine which one of the at least one machine learning models to update.

Abstract: A website building system (WBS) includes a processor implementing a machine learning feedback-based proposal module and a database storing at least the websites of a plurality of users of the WBS, and components of the websites. The module includes a plurality of per activity AI units and a feedback system. Each per activity AI unit supports one or more specific activity related to the WBS and provides at least one system suggestion to the users related to its specific activity. Each per activity AI unit includes at least one machine learning model suitable for the activity supported by its per activity AI unit. The feedback system provides a plurality of different kinds of feedback from the users for updating the machine learning models. The feedback system analyzes the feedback to determine which one of the at least one machine learning models to update.

Abstract: A website building system (WBS) includes a processor implementing a machine learning feedback-based proposal module and a database storing at least the websites of a plurality of users of the WBS, and components of the websites. The module includes a plurality of per activity AI units and a feedback system. Each per activity AI unit supports one or more specific activity related to the WBS and provides at least one system suggestion to the users related to its specific activity. Each per activity AI unit includes at least one machine learning model suitable for the activity supported by its per activity AI unit. The feedback system provides a plurality of different kinds of feedback from the users for updating the machine learning models. The feedback system analyzes the feedback to determine which one of the at least one machine learning models to update.

Abstract: A system comprising a computer-readable storage medium storing at least one program, and a method for reducing cyber-security related false positive alerts is presented. In example embodiments the method may include identifying an indication of a cyber-security threat based on an operational anomaly in a network system. The method may further include determining that the operational anomaly is a false positive indicator with respect to the cyber-security threat based on the operational anomaly being correlated with a malfunction or reconfiguration event.

Abstract: A system comprising a computer-readable storage medium storing at least one program, and a method for reducing cyber-security related false positive alerts is presented. In example embodiments the method may include identifying an indication of a cyber-security threat based on an operational anomaly in a network system. The method may further include determining that the operational anomaly is a false positive indicator with respect to the cyber-security threat based on the operational anomaly being correlated with a malfunction or reconfiguration event.

Abstract: A system comprising a computer-readable storage medium storing at least one program, and a method for reducing cyber-security related false positive alerts is presented. In example embodiments the method may include identifying an abnormal operation pattern in the network system that may signal a cyber-security threat. In response to identifying the abnormal operation pattern, data related to a state change of an asset included in the network system is accessed. The method may further include determining that the abnormal operation pattern and the state change of the asset are correlated, and based on this determination, determining that the abnormal operation pattern is a false positive indicator with respect to the cyber-security threat.

Abstract: A system comprising a computer-readable storage medium storing at least one program, and a method for reducing cyber-security related false positive alerts is presented. In example embodiments the method may include identifying an abnormal operation pattern in the network system that may signal a cyber-security threat. In response to identifying the abnormal operation pattern, data related to a state change of an asset included in the network system is accessed. The method may further include determining that the abnormal operation pattern and the state change of the asset are correlated, and based on this determination, determining that the abnormal operation pattern is a false positive indicator with respect to the cyber-security threat.

Abstract: Methods and systems to provide a hanging protocol including three-dimensional manipulation for display of clinical images in an exam are disclosed. An example method includes detecting selection of a new image exam for display by a user. The example method includes automatically identifying at least one of a) a previously learned hanging protocol saved for the user and b) a saved hanging protocol associated with a prior image exam corresponding to the new image exam. The example method includes applying the saved hanging protocol to the new image exam, the saved hanging protocol including three-dimensional manipulation to be automatically applied to the new image exam as part of the hanging protocol configuration for display. The example method includes facilitating display of the new image exam based on the saved hanging protocol.

Abstract: A novel and useful mechanism for generating a fly-through review for digital images such as tissue sample scans. A fly-through path based on the sample image is determined and one or more fly-through curves are generated. Two-dimensional image manipulations are applied to the sample image in accordance with the one or more fly-through curves and any user preferences to generate a sequence of frame images to be displayed.

Abstract: Certain embodiments of the present invention provide methods and systems for determining a hanging protocol for display of clinical images in a study. Certain embodiments provide a machine learning hanging protocol analysis system. The example system includes an image processing module to process image data to provide one or more features. The example system includes a learning engine to receive processed image data and additional data to learn and adapt a hanging protocol for repeated use by applying one or more machine learning algorithms to the processed image data and additional data. The learning engine is to continue to refine an available selection of candidate layouts based on the processed image data and additional data to provide one or more layout choices for selection to form a hanging protocol for display of image and other data.

Abstract: Example methods, apparatus and articles of manufacture to adaptively reconstruct medical diagnostic images are disclosed. A disclosed example method includes storing non-reconstructed image data captured by a medical image acquisition system, receiving a parameter representing a region of interest from a diagnostic imaging workstation, and communicating a portion of the non-reconstructed image data associated with the region of interest to the diagnostic imaging workstation in response to receiving the parameter, wherein the portion of the non-reconstructed image data is processed by the diagnostic imaging workstation to form a medical diagnostic image.

Abstract: A novel and useful mechanism for generating a fly-through review for digital images such as tissue sample scans. A fly-through path based on the sample image is determined and one or more fly-through curves are generated. Two-dimensional image manipulations are applied to the sample image in accordance with the one or more fly-through curves and any user preferences to generate a sequence of frame images to be displayed.

Abstract: Example methods, apparatus and articles of manufacture to form a wavelet representation of a pathology slide having glass and tissue regions are disclosed. A disclosed example method includes capturing a digital image of a pathology slide, identifying a portion of the digital image that represents a glass portion of the slide, and storing a value representing that the wavelet coefficients for the identified glass portion of the slide are unused without computing a wavelet transform for the identified glass portion.

Abstract: A novel and useful mechanism for generating a fly-through review for digital images such as tissue sample scans. A fly-through path based on the sample image is determined and one or more fly-through curves are generated. Two-dimensional image manipulations are applied to the sample image in accordance with the one or more fly-through curves and any user preferences to generate a sequence of frame images to be displayed.

Abstract: Example methods and apparatus to perform multi-focal plane image acquisition and compression are disclosed. A disclosed example method includes capturing a first image of a portion of an object at a first focal plane and at a first resolution, computing a contrast metric for the captured first image, comparing the contrast metric to a threshold to determine whether to capture a second image of the portion of the object at the first focal plane and at a second resolution, wherein the second resolution is different from the first resolution, capturing the second image of the portion of the object at the first focal plane and at the second resolution, and storing a first representation of the second image in a file, the file containing a second representation of the portion of the object at a second focal plane, wherein the second representation is at the first resolution.

Abstract: A Picture Archiving and Communications System (PACS) transmits medical image information from a server to a viewing workstation. The mode of transmission that the system uses depends on a performance metric of the network. If the network is fast and stable, the entire DICOM image file is transmitted. If the network is not fast and stable, one of several other modes is used to transmit the image information.

Abstract: A novel and useful system and method of detecting the best candidate frames for diagnosis out of a series of coronary angiograms frames. The mechanism analyzes the motion of the visible arteries in the sequence of angiogram frames to identify the local minimas of the differences between sequential frames. Wavelet transform coefficients are generated for each frame and used to quantify the differences between every two sequential frames to detect minimal differences (which correspond to minimal motion). The optimal end-systole and end-diastole frames are selected from these local minima frames.

Abstract: Methods and systems to provide a hanging protocol including three-dimensional manipulation for display of clinical images in an exam are disclosed. An example method includes detecting selection of a new image exam for display by a user. The example method includes automatically identifying at least one of a) a previously learned hanging protocol saved for the user and b) a saved hanging protocol associated with a prior image exam corresponding to the new image exam. The example method includes applying the saved hanging protocol to the new image exam, the saved hanging protocol including three-dimensional manipulation to be automatically applied to the new image exam as part of the hanging protocol configuration for display. The example method includes facilitating display of the new image exam based on the saved hanging protocol.