Decision support technology is provided for use with patients who may experience respiratory deterioration. A mechanism is provided to determine whether a patient is experiencing (or is likely to experience at a future time) an autoimmune inflammatory event, which may include performing a spectral analysis on a time series of nocturnal or axillary temperatures for the patient to determine a spectrum slope or intercept. The time series may be demeaned, detrended, and apodized before performing the spectral analysis. A comparison of the slope or intercept with a baseline value is used to determine an indication of the patient's likely condition or future condition regarding the autoimmune inflammatory event. Based on the comparison, an intervening action may be invoked, such as alerting a caregiver, providing a recommendation or modified treatment, or determining and recommending a tailored prescription of medicine for the patient.

Decision support technology is provided for use with patients who may experience respiratory deterioration. A mechanism is provided to determine whether a patient is experiencing (or is likely to experience at a future time) an autoimmune inflammatory event, which may include performing a spectral analysis on a time series of nocturnal or axillary temperatures for the patient to determine a spectrum slope or intercept. The time series may be demeaned, detrended, and apodized before performing the spectral analysis. A comparison of the slope or intercept with a baseline value is used to determine an indication of the patient's likely condition or future condition regarding the autoimmune inflammatory event. Based on the comparison, an intervening action may be invoked, such as alerting a caregiver, providing a recommendation or modified treatment, or determining and recommending a tailored prescription of medicine for the patient.

A method and system of graph feature extraction and graph classification based on adjacency matrix is provided. The invention first concentrates the connection information elements in the adjacency matrix into a specific diagonal region of the adjacency matrix which reduces the non-connection information elements in advance. Then the subgraph structure of the graph is further extracted along the diagonal direction using the filter matrix. Further, it uses a stacked convolutional neural network to extract a larger subgraph structure. On one hand, it greatly reduces the amount of computation and complexity, getting rid of the limitations caused by computational complexity and window size. On the other hand, it can capture large subgraph structure through a small window, as well as deep features from the implicit correlation structures at both vertex and edge level, which improves speed and accuracy of graph classification.

A search query is received from a search engine of multiple search engines. One or more search results from each search engine of the multiple search engines in response to the search query are received. Each search result of the one or more search results includes a first search score. A factor is determined for each search result of the one or more search results. A second search score is determined for each search result of the one or more search results based on the first search score and the factor. The one or more search results are displayed to a user of the search engine in an order. The order is based on the second search score.

Methods and systems are provided to determine suitable hyperparameters for a machine learning model and/or feature engineering process. A suitable machine learning model and associated hyperparameters are determined by analyzing a dataset. Suitable hyperparameter values for compatible machine learning models having one or more hyperparameters in common and a compatible dataset schema are identified. Hyperparameters may be ranked according to each of their respective influences on a model performance metrics, and hyperparameter values identified as having greater influence may be more aggressively searched.

A method includes obtaining identifiers of entities and symbolic artificial intelligence (AI) models configured to produce outputs responsive to inputs based on events caused by at least one of the entities. At least some of the entities are associated with outputs of respective symbolic AI models and have respective scores corresponding to the respective outputs of the symbolic AI models. The method may include obtaining scenarios, where each scenario includes simulated inputs corresponding to one or more simulated events, and at least some scenarios include a plurality of simulated inputs. The method may also include determining a population of scores of a given entity among the entities, where respective members of the population of scores correspond to respective outputs of the plurality of symbolic AI models, and where the respective outputs correspond to respective scenarios among the scenarios and storing the population of scores in memory.

A computer implemented method for enabling a payment transaction in a computer system executed at least partially by a computer of a user connected via a communication network to a remote computer comprising a database of payment-related data, said method comprising the steps of: a) accessing the payment-related data of a user from within the database, wherein a web browser extension on the user's computer is invoked by the user clicking on a web browser extension graphical user interface (GUI) widget displayed on the user's computer, wherein secure network access is established to access the user's payment-related data from within the database; b) presenting the user's payment-related data via a pop-up window displayed on the user's computer, without requiring application programming interface integration with a website or a web application of a payee, and without requiring a form re-direct away from the website or the web application of the payee; c) enabling the payment transaction, wherein the web browser extension invokes an auto-complete function to automatically populate fields of a checkout form presented from the website or the web application of the payee with the user's payment-related data.

Methods, systems and programming for providing query suggestions based on user feedback. In one example, a prefix of a query is first received. An input including a prefix of a query is received from a user in a search session. A plurality of query suggestions are fetched based on the prefix of the query. Rankings of the plurality of query suggestions are determined based, at least in part, on the user's previous interactions in the search session with respect to at least one of the plurality of query suggestions. The at least one of the plurality of query suggestions has been previously provided to the user in the search session. The plurality of query suggestions are provided in the search session based on their rankings as a response to the input.

The systems and methods include operations for: storing, by one or more processors, a plurality of content items in association with a content item generation template, each of the plurality of content items having been previously generated by a respective user of a plurality of users of a messaging application in accordance with instructions associated with the content item generation template; ranking the plurality of content items associated with the content item generation template; receiving input that selects an identifier of the content item generation template; and displaying the ranked plurality of content items to a given user of the messaging application in response to receiving the input.

Embodiments of the present invention assist in the development, management, and deployment of aggregated data attributes for multiple data sources. One embodiment provides a development interface that allows for elements of attributes, including filters, to be moved into a coding area in which an attribute or an attribute element is being edited. In another embodiment, the user interface presents data fields to assist in the development of filters for multiple data sources with divergent formats. The application further provides a validation interface through which users can validate attributes and trace the results returned by various elements referenced by the attributes under validation. Another embodiment provides a system for managing attributes and deploying them to various systems by creating a deployment file that is used by an attribute calculation system. In one embodiment, the attribute calculation system is a scalable system that dynamically calculates attributes for multiple data sources.