Abstract: Systems and methods are provided for obtaining raw mass spectrometry data from samples, determining signals present across the samples, determining a bin value to apply to the filtered mass spectrometry data, and after determining the bin value, generating an image-based representation of the raw mass spectrometry data, wherein the image-based representation indicates frequencies of peak intensities in each bin.

Abstract: Systems and methods for machine learning model retraining is described. In one example, a system includes a computing device that is configured to determine an anomaly score from a first input of a featurized data set for a machine learning model of a deployment environment. The computing device is configured to determine a feature correlation score for the machine learning model based at least in part on a second input of a featurized historical data set for the machine learning model. A model retraining frequency time period for the machine learning model is determined based at least in part on the feature correlation score and the anomaly score.

Abstract: The present disclosure relates generally to systems and methods for identifying and qualifying microbial species, such as those isolated from a human individual. Once the individual is identified as be deficient in certain microbial species, care can be given accordingly to increase the microbial species and thus improve health of the individual.

Abstract: Systems and methods are provided for obtaining raw mass spectrometry data from samples, determining signals present across the samples, determining a bin value to apply to the filtered mass spectrometry data, and after determining the bin value, generating an image-based representation of the raw mass spectrometry data, wherein the image-based representation indicates frequencies of peak intensities in each bin.

Abstract: Systems and methods for generating digital content and selecting targets for presentation of digital content using artificial intelligence are disclosed. In one example, a nanosegment of customers can be selected as targets for digital content based on their propensity to accept offers for a given campaign. By incorporating a nanosegment-based classification of customers, there can be significantly reduced memory usage by the system, since the customer base will be reduced to a fewer number of groups, and each group more specifically targets traits for one cluster of customers. Attributes of the selected customers can be used to automatically design and generate digital content, such as personalized offers for distribution to the customers, including AI-generated taglines, content, and images. Feedback from each cycle of the campaign can be fed back into subsequent cycles to continuously improve performance and offer outcomes.

Abstract: A method of treating a mammalian subject having hematologic, non-tumorous cancer cells is disclosed. The method comprises the steps of: (A) administering to such a mammalian subject a therapeutically effective amount of a halogenated xanthene, a pharmaceutically acceptable salt or a C1-C4 alkyl ester thereof as a first cancer cytotoxic agent dissolved or dispersed in a pharmaceutically acceptable aqueous medium. The mammalian subject is maintained for a period of time sufficient to induce death of hematologic, non-tumorous cancer cells. A contemplated administration is typically repeated. A contemplated treatment method can also be carried out in conjunction with administration to said mammalian subject of a second therapeutically effective amount of a second, differently-acting cancer cytotoxic agent dissolved or dispersed in a pharmaceutically acceptable medium. The second cancer cytotoxic agent can be a small molecule or an intact antibody or paratope-containing portion thereof.

Abstract: A method of treating a pediatric cancerous solid tumor in a mammalian subject is disclosed that comprises intralesionally administering an amount of a halogenated xanthene or a pharmaceutically acceptable salt thereof, preferably Rose Bengal disodium, that elicits ablation of tumor cells of the administered tumor. Another contemplated method comprises the steps of intralesionally administering an amount of a halogenated xanthene or a pharmaceutically acceptable salt thereof, preferably Rose Bengal disodium, that elicits ablation of tumor cells of the administered tumor and systemically administering a tumor-inhibiting effective amount of a systemic anti-cancer medication that provides synergistic cytotoxicity with the halogenated xanthene. The two administrations can occur concurrently, or one prior to the other.

Abstract: A method of treating a pediatric cancerous solid tumor in a mammalian subject is disclosed that comprises intralesionally administering an amount of a halogenated xanthene or a pharmaceutically acceptable salt thereof, preferably Rose Bengal disodium, that elicits ablation of tumor cells of the administered tumor. Another contemplated method comprises the steps of intralesionally administering an amount of a halogenated xanthene or a pharmaceutically acceptable salt thereof, preferably Rose Bengal disodium, that elicits ablation of tumor cells of the administered tumor and systemically administering a tumor-inhibiting effective amount of a systemic anti-cancer medication that provides synergistic cytotoxicity with the halogenated xanthene. The two administrations can occur concurrently, or one prior to the other.

Abstract: A method of treating a mammalian subject having hematologic, non-tumorous cancer cells is disclosed. The method comprises the steps of: (A) administering to such a mammalian subject a therapeutically effective amount of a halogenated xanthene, a pharmaceutically acceptable salt or a C1-C4 alkyl ester thereof as a first cancer cytotoxic agent dissolved or dispersed in a pharmaceutically acceptable aqueous medium. The mammalian subject is maintained for a period of time sufficient to induce death of hematologic, non-tumorous cancer cells. A contemplated administration is typically repeated. A contemplated treatment method can also be carried out in conjunction with administration to said mammalian subject of a second therapeutically effective amount of a second, differently-acting cancer cytotoxic agent dissolved or dispersed in a pharmaceutically acceptable medium. The second cancer cytotoxic agent can be a small molecule or an intact antibody or paratope-containing portion thereof.

Abstract: Systems and methods are provided for obtaining raw mass spectrometry data from samples, determining signals present across the samples, determining a bin value to apply to the filtered mass spectrometry data, and after determining the bin value, generating an image-based representation of the raw mass spectrometry data, wherein the image-based representation indicates frequencies of peak intensities in each bin.

Abstract: Systems and methods are provided for obtaining raw mass spectrometry data from samples and generating an image representation of the mass spectrometry data. The image representation illustrates frequencies of occurrence of respective signals across the samples. A portion of the mass spectrometry data is obtained or extracted based on the frequencies. This portion is divided into segments. The segments correspond to different ranges or bins of retention times and mass-to-charge ratios. Veracities of signals within the segments are determined using a machine learning model. A subset of the segments that correspond to true signal is extracted. Mass-to-charge ratios and retention times corresponding to the subset of the segments are extracted.

Abstract: Systems and methods are provided for obtaining raw mass spectrometry data from samples, generating an image representation from the raw mass spectrometry data, selecting a portion of the signals corresponding to the image representation, inputting the selected portion into a machine learning model to determine or infer an existence or an absence of signals within respective retention time windows, obtaining a retention time window within which a subset of the signals exist, determining whether to expand the retention time window, determining or receiving an indication of a retention time window within which a subset of the signals are located, and determining whether to expand the retention time window. The systems and methods may selectively expand the retention time window based on the determination, and retrieve information within the expanded retention time window or the retention time window.

Abstract: Systems and methods are provided for obtaining raw mass spectrometry data from samples, determining true signals from the raw mass spectrometry data, determining intensities corresponding to the true signals, adjusting the determined intensities, and based on the adjusted intensities, determining concentrations of one or more constituents corresponding to the true signals.

Abstract: Systems and methods are provided for obtaining raw mass spectrometry data from samples, extracting a subset of the raw mass spectrometry data based on storage characteristics of the computing system, storing the subset of the raw mass spectrometry data within a storage of the computing system, and transmitting the stored subset to a machine learning component.

Abstract: Systems and methods are provided for obtaining raw mass spectrometry data from samples, determining signals present across the samples, and separating the raw mass spectrometry data into discrete intervals in each of the samples. At each interval of the discrete intervals of the raw mass spectrometry data, a local highest intensity signal, relative to any other signal within each interval, is determined, and a frequency of occurrence of each local highest intensity signal across the samples is determined. A subset of local highest intensity signals is retrieved based on respective frequencies of occurrence of the local highest intensity signals. The subset of the local highest intensity signals is ingested into a machine learning model.

Abstract: Provided is a method including obtaining a plurality of time series data sets and a synthetic time series data set that is associated with a first machine learning label such that the first machine learning label is associated with a first time series data set of the plurality of time series data sets. The method includes inputting the synthetic time series data set, the first machine learning label, a second machine learning label that is associated with a second time series data set of the plurality of time series data sets, and a series of generated values in a time series simulation machine learning model that includes a trained generative adversarial network. The method includes running a generator neural network included in the trained generative adversarial network with the inputs and then generating a synthetic second time series data set for the second time series data set.

Abstract: One embodiment provides a method, including: utilizing at least one processor to execute computer code that performs the steps of: providing, on a display device, a communications window, wherein the communications window comprises a request for user input to start a conversation with an online assistant; receiving a user input identifying a request by the user to be completed by the online assistant; updating, based upon the request, the communications window, wherein the updated communications window comprises a summary of the conversation including prepopulated variable terms and allows user interaction to adjust the summary including adjustment of the prepopulated variable terms; and iteratively updating the communications windows based upon user input adjusting the summary. Other aspects are described and claimed.

Abstract: Provided are a computer program product, system, and method for generating constraints based on reported crop arrivals to marketplaces and remote sensed data to estimate farm yields of farm fields. A total arrival quantity constraint for a marketplace is generated comprising a function of a reported arrival of crops at a marketplace and an estimated arrival to the marketplace comprising a sum of farm yields for the farm fields, wherein the farm yields comprise variables to optimize. Sensed data of the farm fields is used to determine relationships of the farm yields for the farm fields. Comparative farm yield constraints are generated comprising relationships of the farm yields for different pairs of farms. A constraint optimization problem is solved based on the total arrival quantity constraint and comparative farm yield constraints to calculate the farm yields of the farm fields.

Abstract: A context sensitive slider content area provides a slide out mechanism that is automatically actuated when additional information is needed during a chat session between an agent and a visitor, e.g. where a pre-chat and/or exit form is to be completed. The context sensitive slide out content area also provides problem resolution information to the visitor to help in solving problems, e.g. the top five problems; and also provides a self-service step-by-step wizard. A history section is provided with which the visitor can track back all previous steps carried out within the smart client. A history bar provides an iconic representation of all previous activities. A technique is also disclosed for executing various actions, such as form filling or requests for additional services, in a chat session.

Abstract: A method of treating a mammalian subject having hematologic, non-tumorous cancer cells is disclosed. The method comprises the steps of: (A) administering to such a mammalian subject a therapeutically effective amount of a halogenated xanthene, a pharmaceutically acceptable salt or a C1-C4 alkyl ester thereof as a first cancer cytotoxic agent dissolved or dispersed in a pharmaceutically acceptable aqueous medium. The mammalian subject is maintained for a period of time sufficient to induce death of hematologic, non-tumorous cancer cells. A contemplated administration is typically repeated. A contemplated treatment method can also be carried out in conjunction with administration to said mammalian subject of a second therapeutically effective amount of a second, differently-acting cancer cytotoxic agent dissolved or dispersed in a pharmaceutically acceptable medium. The second cancer cytotoxic agent can be a small molecule or an intact antibody or paratope-containing portion thereof.