Abstract: A method for improving a physician's workflow by optimizing the physician's access to patient data during a visit of patients to a medical facility includes an electronic medical record (EMR) processor implementing a Health Value Analytics (HVA) component and receiving inputs from EMR/HVA devices. In response, the EMR processor creates value baselines for patient visits, generates a health care value continuum based on a visit of a first patient to the medical facility, and generates a comparison of the health care value continuum to a value baseline, detects a location, on a display screen of the EMR/HVA device, of an EMR record for the first patient; provides the comparison for display in a location adjacent to the displayed EMR record for the first patient; detects replacement of the EMR record with an EMR record for a second patient; and in response to the replacement, discontinues display of the HVA page.

Abstract: A computer-implemented method to establish a relative importance of an input parameter pj in a plurality of input parameters pi in a data set input to a machine learning model, the data set represented by a j row by k column matrix Im, an intersection of each row with each column defining an element, the method includes for each of the plurality of parameters pi in the input data set, a computer sorts columns ki of the matrix Im. to produce a re-ordered matrix Im,j; the computer determines a hyper-parameter N* of sub-matrices into which may be sorted the values in a jth row of the re-ordered matrix Im,j; the computer generates a plurality of group sub-matrices Gi, each of the group sub-matrices comprising a subset of columns and the jth row; the computer inputs the re-ordered matrix Im,j into a fully-trained machine learning model to produce machine learning model outputs; and the computer produces normalized mean values of the outputs.

Abstract: A health status platform includes a receiving component that receives a test result a test of a biological sample collected from a human patient. The test result includes an indication of a presence of an infectious disease in the patient, and an identification and a verification of the patient. The platform includes a certificate component that issues a certificate of origin of the biological sample; and a data merging component that cooperates with a venue access manager that controls access to a venue. The data merging component implements a distributed ledger system that stores encrypted test results of the patient and the identification and verification of the patient, and an end-to-end encryption system that receives an encrypted venue access request from a venue access manager, decrypts the access request, determines if an access request is valid, and if valid, provides an encrypted certificate of origin to the venue access manager.

Abstract: A health safety method executed by a processor includes receiving, by the processor, from a medical facility, a certificate of vaccination for a particular disease for an individual, the vaccination conferring immunity to the individual for the disease; receiving by the processor an access request from a venue for the individual; and responding to the venue access request by providing a health safety certification including the certificate of vaccination for the individual and an effective date range of the certificate of vaccination.

Abstract: A health safety method executed by a processor includes receiving, by the processor, from a medical facility, a certificate of vaccination for a particular disease for an individual, the vaccination conferring immunity to the individual for the disease; receiving by the processor an access request from a venue for the individual; and responding to the venue access request by providing a health safety certification including the certificate of vaccination for the individual and an effective date range of the certificate of vaccination.

Abstract: A computer-implemented method analyzes a medical treatment plan for a patient having a medical condition and determines a value of health care of the plan. The method includes a processor executing instructions to enter the patient into an electronic medical records (EMR) system of a medical facility visited by the patient, assign the patient a diagnosis, recording the medical treatment plan, and generate a portal for accessing and displaying the medical treatment plan. The method further includes a health care value analytics (HVA) server accessing and using historical data, generating a value baseline for approved medical treatments of medical conditions addressed by the medical treatment plan, generating one or more HVA data objects that provide a running comparison of the medical treatment plan and the value baseline, and providing the HVA data objects for display through the portal onto an EMR/HVA access device.

Abstract: A health status platform includes a receiving component that receives a test result a test of a biological sample collected from a human patient. The test result includes an indication of a presence of an infectious disease in the patient, and an identification and a verification of the patient. The platform includes a certificate component that issues a certificate of origin of the biological sample; and a data merging component that cooperates with a venue access manager that controls access to a venue. The data merging component implements a distributed ledger system that stores encrypted test results of the patient and the identification and verification of the patient, and an end-to-end encryption system that receives an encrypted venue access request from a venue access manager, decrypts the access request, determines if an access request is valid, and if valid, provides an encrypted certificate of origin to the venue access manager.

Abstract: A method for evaluating a relative contribution of a first group of J data sets in a collection of N data sets, wherein N>J, includes first applying the collection of N data sets and second applying the first group of J data sets to a model and generating one or more observations O on the collection of N data sets and the first group of J data sets, including generating a N NSA curve comprising computing, using the model, an observation ON on the collection of N data sets; and generating a N?J NSA curve for the first group of J data sets by removing the first group of J data sets from the collection of N data sets, and generating, using the model, an observation ON?J with the first group of J data sets removed. The method then includes generating a measure MJ of contributions of the group of J data sets based on the N NSA curve and the N?J NSA curves.

Abstract: A method for evaluating a relative contribution of a first group of J data sets in a collection of N data sets, wherein N>J, includes first applying the collection of N data sets and second applying the first group of J data sets to a model and generating one or more observations O on the collection of N data sets and the first group of J data sets, including generating a N NSA curve comprising computing, using the model, an observation ON on the collection of N data sets; and generating a N?J NSA curve for the first group of J data sets by removing the first group of J data sets from the collection of N data sets, and generating, using the model, an observation ON?J with the first group of J data sets removed. The method then includes generating a measure MJ of contributions of the group of J data sets based on the N NSA curve and the N?J NSA curves.

Abstract: A data evaluation method includes a processor receiving data sets N, each of which has one or more parameters, applying the data sets N to a machine learning model and generating observations on the data sets N; and executing a network sensitivity analysis (NSA) that includes generating a N NSA curve for each of k distinct parameters in the N data sets including computing an observation ON with the data sets, and generating a N?j NSA curve for each of the of the k distinct parameters. Generating a N?J NSA curve includes removing the jth data set from the N data sets and computing an observation ONj. Executing the NSA further includes determining a contribution of a jth data set based on the k N NSA curves and the k N?j NSA curves; and computing a relative strength Sj of each of the N data sets.

Abstract: A computer-implemented method analyzes a medical treatment plan for a patient having a medical condition and determines a value of health care of the plan. The method includes a processor executing instructions to enter the patient into an electronic medical records (EMR) system of a medical facility visited by the patient, assign the patient a diagnosis, recording the medical treatment plan, and generate a portal for accessing and displaying the medical treatment plan. The method further includes a health care value analytics (HVA) server accessing and using historical data, generating a value baseline for approved medical treatments of medical conditions addressed by the medical treatment plan, generating one or more HVA data objects that provide a running comparison of the medical treatment plan and the value baseline, and providing the HVA data objects for display through the portal onto an EMR/HVA access device.

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 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 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 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.