Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to implement one or more encoding and/or decoding techniques.

Abstract: Embodiments relate to system for automatically predicting payer response to claims. In an embodiment, the system receives claim data associated with a claim. The system identifies a set of claim features of the claim data, and generates an input vector with at least a portion of the set of claim features. The system applies the input vector to a trained model. A first portion of the neural network is configured to generate an embedding representing the input vector with a lower dimensionality than the input vector. A second portion of the neural network is configured to generate a prediction of whether the claim will be denied based on the embedding. The system provides the prediction for display on a user interface of a user device. The prediction may further include denial reason codes and a response date estimation to indicate if, when, and why a claim will be denied.

Abstract: Example methods, apparatuses, and/or articles of manufacture are disclosed that may be implemented, in whole or in part, using one or more computing devices to implement one or more self-supervised machine-learning techniques. In a particular implementation, first and second mappings may map features of an electronic document to associated first and second encoded domains.

Abstract: Disclosed are a system, method and apparatus to generate service codes based, at least in part, on electronic documents.

Abstract: Disclosed are a system, method and apparatus to generate service codes based, at least in part, on electronic documents.

Abstract: Disclosed are a system, method and apparatus to generate service codes based, at least in part, on electronic documents.

Abstract: Disclosed are a system, method and apparatus to generate service codes based, at least in part, on electronic documents. In an embodiment, tokens may be embedded in an electronic document based, at least in part, on a linguistic analysis of the electronic document. Likelihoods of applicability of service codes to the electronic document may be determined based, at least in part, on the embedding of tokens.

Abstract: Embodiments relate to system for automatically predicting payer response to claims. In an embodiment, the system receives claim data associated with a claim. The system identifies a set of claim features of the claim data, and generates an input vector with at least a portion of the set of claim features. The system applies the input vector to a trained model. A first portion of the neural network is configured to generate an embedding representing the input vector with a lower dimensionality than the input vector. A second portion of the neural network is configured to generate a prediction of whether the claim will be denied based on the embedding. The system provides the prediction for display on a user interface of a user device. The prediction may further include denial reason codes and a response date estimation to indicate if, when, and why a claim will be denied.

Abstract: Embodiments relate to system for automatically predicting payer response to claims. In an embodiment, the system receives claim data associated with a claim. The system identifies a set of claim features of the claim data, and generates an input vector with at least a portion of the set of claim features. The system applies the input vector to a trained model. A first portion of the neural network is configured to generate an embedding representing the input vector with a lower dimensionality than the input vector. A second portion of the neural network is configured to generate a prediction of whether the claim will be denied based on the embedding. The system provides the prediction for display on a user interface of a user device. The prediction may further include denial reason codes and a response date estimation to indicate if, when, and why a claim will be denied.

Abstract: Embodiments relate to system for automatically predicting payer response to claims. In an embodiment, the system receives claim data associated with a claim. The system identifies a set of claim features of the claim data, and generates an input vector with at least a portion of the set of claim features. The system applies the input vector to a trained model. A first portion of the neural network is configured to generate an embedding representing the input vector with a lower dimensionality than the input vector. A second portion of the neural network is configured to generate a prediction of whether the claim will be denied based on the embedding. The system provides the prediction for display on a user interface of a user device. The prediction may further include denial reason codes and a response date estimation to indicate if, when, and why a claim will be denied.

Abstract: With the advent of touch-free interfaces such as described in the present disclosure, it is no longer necessary for computer interfaces to be in predefined locations (e.g., desktops) or configuration (e.g., rectangular keyboard). The present invention makes use of touch-free interfaces to encourage users to interface with a computer in an ergonomically sound manner. Among other things, the present invention implements a system for localizing human body parts such as hands, arms, shoulders, or even the fully body, with a processing device such as a computer along with a computer display to provide visual feedback on the display that encourages a user to maintain an ergonomically preferred position with ergonomically preferred motions. For example, the present invention encourages a user to maintain his motions within an ergonomically preferred range without have to reach out excessively or repetitively.

Abstract: A variety of methods, systems, devices and arrangements are implemented for use with motion capture. One such method is implemented for identifying salient points from three-dimensional image data. The method involves the execution of instructions on a computer system to generate a three-dimensional surface mesh from the three-dimensional image data. Lengths of possible paths from a plurality of points on the three-dimensional surface mesh to a common reference point are categorized. The categorized lengths of possible paths are used to identify a subset of the plurality of points as salient points.

Abstract: The present invention provides a system and computerized method for receiving image information and translating it to computer inputs. In an embodiment of the invention, image information is received for a predetermined action space to identify an active body part. From such image information, depth information is extracted to interpret the actions of the active body part. Predetermined gestures can then be identified to provide input to a computer. For example, gestures that can be interpreted to mimic computerized touchscreen operation. Also, touchpad or mouse operations can be mimicked.

Abstract: Systems, devices, methods and arrangements are implemented in a variety of embodiments to facilitate motion capture of objects. Consistent with one such system, three-dimensional representations are determined for at least one object. Depth-based image data is used in the system, which includes a processing circuit configured and arranged to render a plurality of orientations for at least one object. Orientations from the plurality of orientations are assessed against the depth-based image data. An orientation is selected from the plurality of orientations as a function of the assessment of orientations from the plurality of orientations.

Abstract: A variety of methods, systems, devices and arrangements are implemented for use with motion capture. One such method is implemented for identifying salient points from three-dimensional image data. The method involves the execution of instructions on a computer system to generate a three-dimensional surface mesh from the three-dimensional image data. Lengths of possible paths from a plurality of points on the three-dimensional surface mesh to a common reference point are categorized. The categorized lengths of possible paths are used to identify a subset of the plurality of points as salient points.

Abstract: A variety of methods, systems, devices and arrangements are implemented for use with motion capture. One such method is implemented for identifying salient points from three-dimensional image data. The method involves the execution of instructions on a computer system to generate a three-dimensional surface mesh from the three-dimensional image data. Lengths of possible paths from a plurality of points on the three-dimensional surface mesh to a common reference point are categorized. The categorized lengths of possible paths are used to identify a subset of the plurality of points as salient points.

Abstract: The present invention provides for a feature-rich parking system and implements a low-cost, low-technology presence at the parking location. In an embodiment, a parking pole is placed adjacent to a parking space where the parking pole includes a code, including a bar code, QR code, or NFC label that is designed to be identified and processed by a mobile communication device such as a cell phone or smart phone. The processed information can then be wirelessly communicated by the mobile communication device to a remotely situated server that can process a payment for the use of the desired parking space.

Abstract: With the advent of touch-free interfaces such as described in the present disclosure, it is no longer necessary for computer interfaces to be in predefined locations (e.g., desktops) or configuration (e.g., rectangular keyboard). The present invention makes use of touch-free interfaces to encourage users to interface with a computer in an ergonomically sound manner. Among other things, the present invention implements a system for localizing human body parts such as hands, arms, shoulders, or even the fully body, with a processing device such as a computer along with a computer display to provide visual feedback on the display that encourages a user to maintain an ergonomically preferred position with ergonomically preferred motions. For example, the present invention encourages a user to maintain his motions within an ergonomically preferred range without have to reach out excessively or repetitively.

Abstract: The present invention provides a system and computerized method for receiving image information and translating it to computer inputs. In an embodiment of the invention, image information is received for a predetermined action space to identify an active body part. From such image information, depth information is extracted to interpret the actions of the active body part. Predetermined gestures can then be identified to provide input to a computer. For example, gestures that can be interpreted to mimic computerized touchscreen operation. Also, touchpad or mouse operations can be mimicked.

Abstract: A variety of methods, systems, devices and arrangements are implemented for use with motion capture. One such method is implemented for identifying salient points from three-dimensional image data. The method involves the execution of instructions on a computer system to generate a three-dimensional surface mesh from the three-dimensional image data. Lengths of possible paths from a plurality of points on the three-dimensional surface mesh to a common reference point are categorized. The categorized lengths of possible paths are used to identify a subset of the plurality of points as salient points.