Abstract: A processor-implemented method for determining and indicating values of medical treatment plans, includes the processor creating value baselines comprising health metric values for approved plans of care; detecting an activity indicating a patient-related event during a visit associated with a patient; generating a health value continuum based on the visit; generating a comparison of the health value continuum to a value baseline; and providing data and instructions to display on a display page, a representation of the health value continuum to value baseline comparison.

Abstract: A processor-implemented method for determining and indicating values of medical treatment plans, includes the processor creating value baselines comprising health metric values for approved plans of care; detecting an activity indicating a patient-related event during a visit associated with a patient; generating a health value continuum based on the visit; generating a comparison of the health value continuum to a value baseline; and providing data and instructions to display on a display page, a representation of the health value continuum to value baseline comparison.

Abstract: A method of valuing a patent using metric characteristics of similar patents granted earlier, whereas said metrics comprise a variety of estimated future characteristics, normalized using estimated future market size. Similar patents are identified using a combination of one or more metric characteristics, for example, patent value estimate, semantic similarity, dependent claim counts, cited patent counts, word counts, patent counts within assigned classes/subclasses, and distinct assignee counts.

Abstract: A computer-based method is described for categorizing inventions within the context of an invention landscape. A set of key phases and/or semantic properties is employed based upon the likelihood that the description of the invention to be categorized will share these key phrases and/or semantic properties with the descriptions of similar inventions from within the invention landscape. The results are ranked in such a way as to enable a tentative assignment of the target invention to one or more categories, and to optionally estimate the value of the invention.

Abstract: A computer-based method is described for categorizing inventions within the context of an invention landscape. A set of key phases is employed based upon the likelihood that the description of the invention to be categorized will share these key phrases with the descriptions of similar inventions from within the invention landscape. The results are ranked in such a way as to enable a tentative assignment of the target invention to one or more categories, and to optionally estimate the value of the invention.

Abstract: A method for deriving patent market value estimates within a patent landscape utilizing a relative metric score for all patents in the landscape, calibrating said market values by using a percentage of the known market values of patent portfolio owners, for example publicly traded companies with known patent portfolios. This method is based on the premise that the patents owned by said entities contribute to the market values of these entities, and describes a complete end-to-end process for estimating the market values for all patents within a patent landscape. This method also includes a set of steps useful for estimating the amount of revenue some patents may generate.

Abstract: A method for assigning a relative score to patents within a patent landscape is described, with the objective of being able to compare any two or more patents. A patent is considered seminal if the novelty of the invention is not a product of variations of prior art and spawns a new direction in intellectual property as described by new patents that come later. The method described in this document is one that combines a number of direct and indirect network factors and tempers the method by considering proximity to other patents within the landscape, incestuous citations, and other metric quantities inherent in the patent documents and from publicly available information. The method described is a relativistic model that is generic in that it does not depend on specific success of any individual patent to produce revenue or to fend off exposure to other specified intellectual property.

Abstract: A method for assigning a relative score to patents within a patent landscape is described, with the objective of being able to compare any two or more patents. A patent is considered seminal if the novelty of the invention is not a product of variations of prior art and spawns a new direction in intellectual property as described by new patents that come later. The method described in this document is one that combines a number of direct and indirect network factors and tempers the method by considering proximity to other patents within the landscape, incestuous citations, and other metric quantities inherent in the patent documents and from publicly available information. The method described is a relativistic model that is generic in that it does not depend on specific success of any individual patent to produce revenue or to fend off exposure to other specified intellectual property.

Abstract: A system for analyzing similarities between a first and second corpus or between a set of concepts and a corpus uses natural language processing and machine intelligence methods to replace terms or phrases in the corpus with concepts, determine the frequency of each concept in the corpus, and convert the corpus into a concept frequency file to enable easy comparison of the two corpuses or easy retrieval of items from the corpus that contain concept. Difference analysis and a combination of content and spectral analysis may be employed.

Abstract: A system for analyzing similarities between a first and second corpus or between a set of concepts and a corpus uses natural language processing and machine intelligence methods to replace terms or phrases in the corpus with concepts, determine the frequency of each concept in the corpus, and convert the corpus into a concept frequency file to enable easy comparison of the two corpuses or easy retrieval of items from the corpus that contain concept. Difference analysis and a combination of content and spectral analysis may be employed.

Abstract: A system for analyzing similarities between a first and second corpus or between a set of concepts and a corpus uses natural language processing and machine intelligence methods to replace terms or phrases in the corpus with concepts, determine the frequency of each concept in the corpus, and convert the corpus into a concept frequency file to enable easy comparison of the two corpuses or easy retrieval of items from the corpus that contain concept. Difference analysis and a combination of content and spectral analysis may be employed.