Abstract: A mechanism computes a discounted health variable with a penalty for deviating from clinical guidelines based on a distance function representing an allowed deviation from the clinical guidelines, applies reinforcement learning techniques on the discounted health variable to generate a reinforcement learning (RL) model for generating dynamic treatment regimes, and determines, for a patient for a plurality of times, a next action in a treatment regime using the RL model with no distance function, an optimal next action in the treatment regime with allowed deviation from the guidelines, and a next action in the treatment regime that adheres to the guidelines. The mechanism generates an outcome output display based on the determined next action in a treatment regime using the RL model with no distance function, optimal next action in the treatment regime with allowed deviation from the guidelines, and next action in the treatment regime that adheres to the guidelines.

Abstract: An example operation may include one or more of connecting to a blockchain configured to store replicated Uniform Resource Locator (URL) shortening tables, receiving an indication from a blockchain node that a destination of a shortened URL has changed, informing other blockchain nodes of the changed destination of the shortened URL, receiving a shortened URL request from the blockchain node and checking if the requested shortened URL on other blockchain nodes points to a same destination, and connecting the blockchain node to the destination of the requested shortened URL if the destination associated with the shortened URL points to the same destination across all the blockchain nodes.

Abstract: A method of managing lifelong learner events on a blockchain includes detecting an event related to a learner using a blockchain-enabled digital learning system, determining a concern/risk level of the learner by performing a risk assessment, determining parameters to generate a transaction related the learner's event based on the parameters and the concern/risk level, determining the values of the parameters by measuring the value or importance of the event and its associated metadata and documents, generating a list of transactions corresponding to the parameters, and validating the transactions using validating distributed peer-to-peer devices that run one or more chaincodes related to the management of the lifelong learner events.

Abstract: An example operation may include one or more of connecting to a blockchain configured to store replicated Uniform Resource Locator (URL) shortening tables, receiving an indication from a blockchain node that a destination of a shortened URL has changed, informing other blockchain nodes of the changed destination of the shortened URL, receiving a shortened URL request from the blockchain node and checking if the requested shortened URL on other blockchain nodes points to a same destination, and connecting the blockchain node to the destination of the requested shortened URL if the destination associated with the shortened URL points to the same destination across all the blockchain nodes.

Abstract: A method of analyzing physiological data streams. According to the method, physiological data is received into a computerized machine. The physiological data comprises numerical data and medical symptoms of a patient. Features are extracted from the physiological data based on development of the physiological data over a period of time. The features are converted into a textual representation using natural language generation. Input terms for an information retrieval system operating on the computerized machine are automatically generated based on the features. The input terms are input to the information retrieval system. A corpus of data is automatically searched to retrieve results to the input terms using the information retrieval system.

Abstract: A method for performing assisted knowledge discovery includes receiving a dataset. Each of a plurality of analytical techniques is applied to the received data set to generate a plurality of corresponding analytical results. A composite validation metric is applied to each of the plurality of analytical results. The composite validation metric is a single scoring/ranking function that is created from a plurality of different scoring/ranking functions. The plurality of analytical results is presented to a user arranged in accordance with the results of the applying the composite validation metric to each of the plurality of analytical results. A selection from the user from among the plurality of analytical results is recorded. The user's selection is used to modify the composite validation metric such that the analytical techniques responsible for generating the selected analytical result is scored/ranked more highly.

Abstract: A method of managing lifelong learner events on a blockchain includes detecting an event related to a learner using a blockchain-enabled digital learning system, determining a concern/risk level of the learner by performing a risk assessment, determining parameters to generate a transaction related the learner's event based on the parameters and the concern/risk level, determining the values of the parameters by measuring the value or importance of the event and its associated metadata and documents, generating a list of transactions corresponding to the parameters, and validating the transactions using validating distributed peer-to-peer devices that run one or more chaincodes related to the management of the lifelong learner events.

Abstract: A method of managing a school system using a blockchain includes receiving a transaction related to a school record along with chaincodes to validate the transaction and a set of record tokens that represent events with respect to a stakeholder, obtaining a historical block identifier from a blockchain of historical school records that is representative of historical record events in the blockchain, receiving validity requirements for the events on the record, obtaining a validation token that is indicative of a validity of the events based on the set of record tokens, computing a chaincode block for the transaction against the one or more validation requirements as a function of the validation token, the historical school record's block identifier, and the set of record tokens, and creating a new block and upadating the blockchain of historical school records based on the new block the transaction, when the validation succeeds,

Abstract: A method of analyzing physiological data streams. According to the method, physiological data is received into a computerized machine. The physiological data comprises numerical data and medical symptoms of a patient. Features are extracted from the physiological data based on development of the physiological data over a period of time. The features are converted into a textual representation using natural language generation. Input terms for an information retrieval system operating on the computerized machine are automatically generated based on the features. The input terms are input to the information retrieval system. A corpus of data is automatically searched to retrieve results to the input terms using the information retrieval system.

Abstract: A method of analyzing physiological data streams. According to the method, physiological data is received into a computerized machine. The physiological data comprises numerical data and medical symptoms of a patient. Features are extracted from the physiological data based on development of the physiological data over a period of time. The features are converted into a textual representation using natural language generation. Input terms for an information retrieval system operating on the computerized machine are automatically generated based on the features. The input terms are input to the information retrieval system. A corpus of data is automatically searched to retrieve results to the input terms using the information retrieval system.

Abstract: A method of meta-learning includes receiving a prediction objective, extracting a plurality of subsets of data from a distributed dataset, generating a plurality of local predictions, wherein each local prediction is based on a different subset of the plurality of subsets of data and the prediction objective, combining the plurality of local predictions, and generating a final prediction based on the combined local predictions.

Abstract: A method for performing assisted knowledge discovery includes receiving a dataset. Each of a plurality of analytical techniques is applied to the received data set to generate a plurality of corresponding analytical results. A composite validation metric is applied to each of the plurality of analytical results. The composite validation metric is a single scoring/ranking function that is created from a plurality of different scoring/ranking functions. The plurality of analytical results is presented to a user arranged in accordance with the results of the applying the composite validation metric to each of the plurality of analytical results. A selection from the user from among the plurality of analytical results is recorded. The user's selection is used to modify the composite validation metric such that the analytical techniques responsible for generating the selected analytical result is scored/ranked more highly.

Abstract: A method of analyzing physiological data streams. According to the method, physiological data is received into a computerized machine. The physiological data comprises numerical data and medical symptoms of a patient. Features are extracted from the physiological data based on development of the physiological data over a period of time. The features are converted into a textual representation using natural language generation. Input terms for an information retrieval system operating on the computerized machine are automatically generated based on the features. The input terms are input to the information retrieval system. A corpus of data is automatically searched to retrieve results to the input terms using the information retrieval system.

Abstract: A method of analyzing physiological data streams. According to the method, physiological data is received into a computerized machine. The physiological data comprises numerical data and medical symptoms of a patient. Features are extracted from the physiological data based on development of the physiological data over a period of time. The features are converted into a textual representation using natural language generation. Input terms for an information retrieval system operating on the computerized machine are automatically generated based on the features. The input terms are input to the information retrieval system. A corpus of data is automatically searched to retrieve results to the input terms using the information retrieval system.

Abstract: One or more embodiments manage emergency response services. An emergency event is determined to have occurred. A set of civilian responders currently available to respond to the emergency event is selected from a plurality of civilian responders in response to determining that the emergency event has occurred. Each civilian responder in the set of civilian responders is associated with at least one wireless communication device. The set of civilian responders is notified that the emergency event has occurred. A set of emergency event information associated with the emergency event is transmitted to at least one wireless communication device associated with each civilian responder in the set of civilian responders.

Abstract: Collaborative program development systems are provided which implement methods for providing automated programming assistance to code developers in a collaborative program development environment. In particular, systems and methods for automated programming assistance are supported by leveraging a database or library of shared code snippets that are classified according to code patterns and rating scores that are derived from feedback and input from various code developers within a collaborative program development environment.

Abstract: One or more embodiments manage emergency response services. An emergency event is determined to have occurred. A set of civilian responders currently available to respond to the emergency event is selected from a plurality of civilian responders in response to determining that the emergency event has occurred. Each civilian responder in the set of civilian responders is associated with at least one wireless communication device. The set of civilian responders is notified that the emergency event has occurred. A set of emergency event information associated with the emergency event is transmitted to at least one wireless communication device associated with each civilian responder in the set of civilian responders.

Abstract: Systems and methods for adaptive signal sampling and sample quantization for resource-constrained stream processing. Exemplary embodiments include a signal sampling and signal quantization method for a data stream from a ECG sensor into a pervasive device, the method including adaptively sampling the data stream, compressing data samples from the data stream, reducing the number of samples via quantization, defining a utility function for signal reconstruction, and formulating optimization on the reconstructed signal that is jointly sampled and quantized.

Abstract: A system and method for predicting patient prognosis includes a similarity module configured in program storage media to provide a similarity function for a data source and compute similarity scores for pairs of patients. An alignment module is configured to align a query patient to a best anchor timestamp of a similar patient or patients so that a comparison between the query patient and at least one similar patient is provided. A prediction module is configured to predict a long-term outcome measure of the query patient based on data from the at least one similar patient.

Abstract: A system and method for predicting near term measurements of a patient includes a stream processor configured to summarize raw measurements from patients into signatures and construct optimal prediction models based on previously obtained signatures. A similar patient tracker is configured to monitor similar patient information for a query patient. The similar patient information is determined based on a similarity between the query patient and signatures of other patients. A model analyzer is configured to employ retrofitted optimal prediction models from similar patients to predict near term measurements of the query patient.