Abstract: Embodiments of the invention include a system and method of using biomarkers in the diagnosis of disease, for example, breast cancer. A subject can be screened for breast cancer based on altered expression of one or more mRNAs in blood, plasma or salvia. Embodiments include 26 specific mRNAs for use as biomarkers to screen or distinguish healthy individuals from individuals affected with breast cancer. Levels of more than one of the mRNAs can be used to create a biomarker fingerprint for early screening of a breast cancer. Embodiments also include a kit for screening healthy subjects from subjects affected with breast cancer.

Abstract: Methods and systems described in this disclosure are directed to authentication of calling parties. The authentication of calling parties applies to simultaneous voice and/or data communications with multiple parties over multiple electronic mediums including a variety of electronic devices. A user can continue to maintain a data exchange session with a representative of an entity offering the goods or services of interest to the user across more than one user device. In some embodiments, a user can invite other parties in a multi-party call involving the user and the representative. Various embodiments for multi-party and multi-device authentication mechanisms are described herein. In some embodiments, the system calculates an estimated call waiting time for a user to speak with the representative.

Abstract: Embodiments include a system and method of using biomarkers in the diagnosis of liver disease. A subject can be screened based on expression of specific mRNAs, miRNAs, proteins or peptides in blood, serum or plasma. Specific mRNAs/miRNAs are used as biomarkers to distinguish healthy individuals from individuals affected with a liver disease. Embodiments include 14 mRNA biomarkers to diagnose NAFL vs. healthy liver (i.e. early detection of liver disease). Embodiments also include 9 mRNA biomarkers to diagnose NAFL vs. NASH (i.e. stage of liver disease progression) and 37 mRNA biomarkers to diagnose NASH. Further embodiments include 32 miRNA biomarkers to diagnose and distinguish between NASH, hepatitis B and hepatitis C. Levels of more than one of the mRNAs, miRNAs or proteins can be scored and compared to one or more threshold values to diagnose or determine the prognosis of a liver disease. Embodiments also include a kit for screening healthy subjects from subjects affected with a liver disease.

Abstract: Systems and methods of determining pre-quantitation attributes of biological samples using post-quantitation attributes of those samples is disclosed. By altering a set of biological samples in a measurable way before running the set through an instrument (e.g., a mass spectrometer), a model can be developed that enables determination of the unknown pre-quantitation attributes in other biological samples as a function of post-quantitation attributes.

Abstract: Embodiments of the invention include a system and method of using biomarkers in the diagnosis of Parkinson's disease. A subject can be screened for Parkinson's disease based on altered expression of one or more biomarkers in blood, plasma or saliva from the subject. Embodiments include 18 specific mRNA biomarkers to screen or distinguish healthy individuals from individuals affected with Parkinson's disease. Embodiments also include 33 specific protein biomarkers to screen or distinguish healthy individuals from individuals affected with Parkinson's disease. The biomarkers can also be used to determine the prognosis of a subject with the disease and identify early-onset and/or asymptomatic Parkinson's disease.

Abstract: Embodiments of the invention include a system and method of using biomarkers in the diagnosis of lung cancer. A subject can be screened for lung cancer based on expression of specific mRNAs, miRNAs or the detection of a nucleic acid, protein, peptide or other biological molecule in blood, serum or plasma. Embodiments include 29 specific miRNAs for use as biomarkers to screen or distinguish healthy individuals from individuals affected with the disease, including a lung cancer, along with 81 additional nucleic acids, proteins or peptides for use as biomarkers to screen or distinguish healthy individuals from individuals affected with the disease, including a lung cancer. Levels of more than one of the mRNAs, miRNAs or proteins can be scored and compared to one or more threshold values to diagnose or determine the prognosis of lung cancer. Embodiments also include a kit for screening healthy subjects from subjects affected with the disease.

Abstract: Response to treatment of an inflammatory condition can be predicted based on characteristics of one or more markers from a subject. The markers can include expressions of nucleotide sequences identified herein and of combinations thereof. A response value can be calculated based on characteristics (e.g., expression levels) of one or more of the markers, as well as other characteristics of the subject, such as baseline clinical data. The treatment can be administered when the response value is beyond a threshold.

Abstract: Embodiments of the invention include a system and method of using biomarkers in the diagnosis of lung cancer. A subject can be screened for lung cancer based on expression of specific mRNAs, miRNAs or the detection of a nucleic acid, protein, peptide or other biological molecule in blood, serum or plasma. Embodiments include 29 specific miRNAs for use as biomarkers to screen or distinguish healthy individuals from individuals affected with the disease, including a lung cancer, along with 81 additional nucleic acids, proteins or peptides for use as biomarkers to screen or distinguish healthy individuals from individuals affected with the disease, including a lung cancer. Levels of more than one of the mRNAs, miRNAs or proteins can be scored and compared to one or more threshold values to diagnose or determine the prognosis of lung cancer. Embodiments also include a kit for screening healthy subjects from subjects affected with the disease.

Abstract: Embodiments of the invention include a system and method of using biomarkers in the diagnosis of lung cancer. A subject can be screened for lung cancer based on expression of specific mRNAs, miRNAs or the detection of a nucleic acid, protein, peptide or other biological molecule in blood, serum or plasma. Embodiments include 29 specific miRNAs for use as biomarkers to screen or distinguish healthy individuals from individuals affected with the disease, including a lung cancer, along with 81 additional nucleic acids, proteins or peptides for use as biomarkers to screen or distinguish healthy individuals from individuals affected with the disease, including a lung cancer. Levels of more than one of the mRNAs, miRNAs or proteins can be scored and compared to one or more threshold values to diagnose or determine the prognosis of lung cancer. Embodiments also include a kit for screening healthy subjects from subjects affected with the disease.

Abstract: Feature selection methods and processes that facilitate reduction of model components available for iterative modeling. It has been discovered that methods of eliminating model components that do not meaningfully contribute to a solution can be preliminarily discovered and discarded, thereby dramatically decreasing computational requirements in iterative programming techniques. This development unlocks the ability of iterative modeling to be used to solve complex problems that, in the past, would have required computation time on orders of magnitude too great to be useful.

Abstract: Feature selection methods and processes that facilitate reduction of model components available for iterative modeling. It has been discovered that methods of eliminating model components that do not meaningfully contribute to a solution can be preliminarily discovered and discarded, thereby dramatically decreasing computational requirements in iterative programming techniques. This development unlocks the ability of iterative modeling to be used to solve complex problems that, in the past, would have required computation time on orders of magnitude too great to be useful.

Abstract: Systems and methods of reducing computation time required to implement iterative model development techniques. Methods of the inventive subject matter are directed to the generation and identification of models having desirable characteristics that can be used to seed iterative model development techniques, thereby reducing required computation time. Models are generated and then various parameters and metrics describing attributes of those models are determined. Model development is ceased depending on one or any combination of the various parameters and metrics.

Abstract: Feature selection methods and processes that facilitate reduction of model components available for iterative modeling. It has been discovered that methods of eliminating model components that do not meaningfully contribute to a solution can be preliminarily discovered and discarded, thereby dramatically decreasing computational requirements in iterative programming techniques. This development unlocks the ability of iterative modeling to be used to solve complex problems that, in the past, would have required computation time on orders of magnitude too great to be useful.

Abstract: Dimensionality reduction in high-dimensional datasets can decrease computation time, and processes for dimensionality reduction may even be useful in lower-dimensional datasets. It has been discovered that methods of dimensionality reduction may dramatically decrease computational requirements in machine learning programming techniques. This development unlocks the ability of computational modeling to be used to solve complex problems that, in the past, would have required computation time on orders of magnitude too great to be useful.

Abstract: Systems and methods of determining pre-quantitation attributes of biological samples using post-quantitation attributes of those samples is disclosed. By altering a set of biological samples in a measurable way before running the set through an instrument (e.g., a mass spectrometer), a model can be developed that enables determination of the unknown pre-quantitation attributes in other biological samples as a function of post-quantitation attributes.

Abstract: This invention comprises a method of simulating an ecological environment, where digital agents within the environment are capable of processing data, and agents that successfully process data are permitted to reproduce to generate new algorithms. The invention is a groundbreaking advance in artificial intelligence and machine learning and enables processes that were once considered computationally impossible.

Abstract: Feature selection methods and processes that facilitate reduction of model components available for iterative modeling. It has been discovered that methods of eliminating model components that do not meaningfully contribute to a solution can be preliminarily discovered and discarded, thereby dramatically decreasing computational requirements in iterative programming techniques. This development unlocks the ability of iterative modeling to be used to solve complex problems that, in the past, would have required computation time on orders of magnitude too great to be useful.

Abstract: Systems and methods of determining pre-quantitation attributes of biological samples using post-quantitation attributes of those samples is disclosed. By altering a set of biological samples in a measurable way before running the set through an instrument (e.g., a mass spectrometer), a model can be developed that enables determination of the unknown pre-quantitation attributes in other biological samples as a function of post-quantitation attributes.

Abstract: Feature selection methods and processes that facilitate reduction of model components available for iterative modeling. It has been discovered that methods of eliminating model components that do not meaningfully contribute to a solution can be preliminarily discovered and discarded, thereby dramatically decreasing computational requirements in iterative programming techniques. This development unlocks the ability of iterative modeling to be used to solve complex problems that, in the past, would have required computation time on orders of magnitude too great to be useful.

Abstract: Feature selection methods and processes that facilitate reduction of model components available for iterative modeling. It has been discovered that methods of eliminating model components that do not meaningfully contribute to a solution can be preliminarily discovered and discarded, thereby dramatically decreasing computational requirements in iterative programming techniques. This development unlocks the ability of iterative modeling to be used to solve complex problems that, in the past, would have required computation time on orders of magnitude too great to be useful.