Abstract: A coordinator module for improving communications within a cloud computing system is disclosed. The coordinator module initiates transaction requests by generating a coordination context, where the coordination context includes a transaction context, a coordination type, and an initiator supplemental address. The coordinator module includes a supplemental address handler for creating the initiator supplemental address that unique identifies the coordinator module and the associated pod. The coordinator module receives transaction responses, where the transaction response includes a coordination context. The coordinator module includes a transaction context checker to verify that the transaction response was not received in error, by comparing the received transaction context with a saved transaction context. The coordinator module includes a registration bridge that identifies an alternate coordinator module and alternate pod to process the transaction response if the transaction contexts do not match.

Abstract: The present disclosure provides a method for preparing lithium iron phosphate from ferric hydroxyphosphate, including: purifying ferrous sulfate to form a ferrous sulfate solution, adding hydrogen peroxide, phosphoric acid, an ammonium dihydrogen phosphate solution and ammonia water into the ferrous sulfate solution and then reacting to form a mixed slurry, holding the mixed slurry at a temperature for a period of time, and then washing with water and subjecting to press filtration to form ferric hydroxyphosphate precursors with different iron-phosphorus ratios; then flash drying, sintering at a high temperature, and pulverizing to obtain ferric hydroxyphosphate precursors with different iron-phosphorus ratios and different specific surface areas.

Abstract: A method for controlling a device for automatically adjusting an airway opening body position is provided. The device includes a horizontal base plate, a head support block, a back support plate, a neck support apparatus, a head cover assembly, and a programmable logic controller (PLC). The neck support apparatus is positioned between the head support block and the back support plate. The PLC is configured to controls a stroke of an electric cylinder according to the following equations: ?=1.235?+?, and ?=KX+B+C, where ? is a body position angle, the body position angle is an angle between a positive projection line of a connecting line from a mandibular angle to an external acoustic meatus on a symmetrical surface of a human body and the back support plate, and ? is a preset value ranging from 90° to 100°.

Abstract: Aspects of the invention include a computer-implemented method including extracting a domain-specific object feature from a first image data, wherein the feature describes an object in the first image data. A domain-specific semantic meaning of text data is determined. The object feature is mapped to a portion of the text data, wherein the portion of the text data describes the object. A joint representation of the object and the portion of the text data is created. A second image data and a query directed towards an object in the second image data is received. An answer to the query is generated based on the joint representation.

Abstract: The disclosure provides a method for data instance processing. The method includes obtaining a set of data instances collected from a plurality of organizations. Each of the data instances includes at least one record formed in an organization that stores values of a plurality of attributes of the data instance. The method also includes dividing the set of data instances into groups, wherein data instances with conflicting values for the same attribute are divided into different groups. The method further includes subdividing data instances in each of the groups into clusters.

Abstract: A method, a system and a computer program product may evaluate reduction of disease risk. Patient data of a patient may be received. A selection of a disease outcome may be received. A risk score that the patient will experience the selected disease outcome may be determined. The determining may use the patient data. Intervention options may be generated based on the patient data and by accessing a medical record data structure. An intervention effect for each of the intervention options may be determined. The intervention effect may change the risk score. The intervention effects may be compared. A recommendation of at least one of the intervention options may be provided based on the comparing of the intervention effects.

Abstract: Embodiments of the present disclosure relate to methods, systems, and computer program products for observation data evaluation. In a method, a hierarchical relationship between a plurality of observation items is obtained based on a dataset including a plurality of observation samples. Here, an observation sample in the plurality of observation samples includes a group of measurements for the group of observation items, respectively. A plurality of evaluation models for evaluating an observation sample is generated based on the hierarchical relationship according to a predefined group of membership functions and a predefined group of fuzzy operators. An evaluation model is selected for a further evaluation from the plurality of evaluation models based on a plurality of confidence intervals for the plurality of evaluation models. With these embodiments, the evaluation model may be obtained in an easy and more effective way.

Abstract: This disclosure relates to a method, a system and a computer program product for synthesizing risk prediction models to generate a generalized risk prediction model for a particular disease. The method comprises retrieving a plurality of literatures from one or more databases. Each of the plurality of literatures defines a risk prediction model for a same disease. The method further comprises extracting study features from each of the plurality of literatures. The method further comprises extracting weights of risk factors in the risk prediction model defined by each of the plurality of literatures from the plurality of literatures. The method further comprises calculating adjusted weights of risk factors based on the extracted study features and the extracted weights of risk factors, to form an adjusted risk prediction model.

Abstract: A model learning and sample value generating framework includes a system and method to comprehensively integrate encoding, decoding and value predicting, and optimizing functions to reconstruct as accurate as possible an original input sample data space. The system leverages a variational autoencoder model to generate as realistic samples of that data space as possible. The system learns a value prediction function to achieve a target outcome based on the latent feature data instead of the original input data. Further, the system solves the optimization problem in the latent space without constraints to avoid the difficulty in optimizing in the original sample data space. The generated optimal samples are as similar as possible to the real-world input samples. The system provides a flexible data generation mechanism which is suitable for various kinds of target outcome specifications.

Abstract: A computer-implemented method for predicting non-communicable diseases with infectious risk factors using artificial intelligence includes detecting one or more risk factors associated with a non-communicable disease based on a graph associated with person-to-person links, generating a data structure for compactly representing the graph to compute at least one person-to-person distance, and performing a machine learning technique with regularization of the at least one person-to-person distance.

Abstract: The present invention discloses a preparation method for a surface molding film of a PVC-based stone plastic composite board, including: surface activation treatment of the PVC-based stone plastic composite board: preparation of an activated putty, coarse roughening of a substrate surface, application and solidification of the activated putty, and fine roughening of the substrate surface; preparation of a PMMA slurry; and surface film forming of the PVC-based stone plastic composite board. The PVC-based stone plastic composite board coated with a PMMA film is obtained by cold pressing and shaping in a mold, tightening up a clamp, solidifying at low temperature, treating at high temperature, cooling and demolding.

Abstract: Aspects of the invention include a computer-implemented method including extracting a domain-specific object feature from a first image data, wherein the feature describes an object in the first image data. A domain-specific semantic meaning of text data is determined. The object feature is mapped to a portion of the text data, wherein the portion of the text data describes the object. A joint representation of the object and the portion of the text data is created. A second image data and a query directed towards an object in the second image data is received. An answer to the query is generated based on the joint representation.

Abstract: A method, a system and a computer program product may evaluate reduction of disease risk. Patient data of a patient may be received. A selection of a disease outcome may be received. A risk score that the patient will experience the selected disease outcome may be determined. The determining may use the patient data. Intervention options may be generated based on the patient data and by accessing a medical record data structure. An intervention effect for each of the intervention options may be determined. The intervention effect may change the risk score. The intervention effects may be compared. A recommendation of at least one of the intervention options may be provided based on the comparing of the intervention effects.

Abstract: Embodiments of the present disclosure relate to a method, system, and computer program product for domain adaptation. According to the method, a source model of a source domain is obtained, where the source model is trained to generate a label indicating a predicted category of data from the source domain. A training sample from a target domain is obtained, where the training sample comprises training data from the target domain and a true label indicating a true category of the training data from the target domain. A first label is generated for the training data by using the source model. The first label indicates a predicted category of the training data. A target model of the target domain is trained based on the training data, the true label and the first label.

Abstract: The present disclosure relates to a method, system and computer program product for electronic health record (EHR) data synthetization. According to the method, an original EHR dataset X is captured. A latent space Z is generated from the original EHR dataset X, wherein dimensionality of Z is lower than that of X. A stochastic process prior module is applied to the latent space Z. Synthetic EHR dataset X? is reconstructed from the latent space Z after being applied with the stochastic process prior.

Abstract: Systems, computer-implemented methods and/or computer program products that facilitate predicting personalized risks based on intrinsic factors and extrinsic factors are provided. In one example, a computer-implemented method comprises: collecting, by a system operatively coupled to a processor, intrinsic factors and extrinsic factors associated with infectious diseases; generating, by the system, a probabilistic model based on the intrinsic factors and extrinsic factors, wherein the model incorporates node characteristics into infection probability; and refining, by the system, the model through concurrently learning respective node thresholds and hidden infection network structure of the model.

Abstract: A computer implemented method identifies guidelines through use of a neural network by a remote guideline server. A client computer transmits instructions to the remote guideline server to retrieve and evaluate multiple candidate guidelines. The remote guideline server utilizes a neural network to identify a string of terms found in each of the multiple candidate guidelines that match one or more strings of terms from a model guideline; to identify a semantic concept of each of the multiple candidate guidelines that matches one or more semantic concepts from the model guideline; and to identify a structural pattern of each of the multiple candidate guidelines that matches one or more structural patterns of the model guideline. The candidate guidelines that match the model guideline are then sent from the remote guideline server to the client computer.

Abstract: Techniques for regression analysis of optimization potential are provided. An actionable set of data elements is identified in operational data, where the operational data comprises a plurality of data elements. A regression model is generated based on the operational data, where the regression model defines a contribution weight for at least a first data element of the actionable set of data elements. A first expected value is determined for the first data element based on industry data. A potential optimization for the first data element is then quantified, based at least in part on the first expected value and the contribution weight of the first data element.

Abstract: Patient treatment may be optimized using Recurrent Neural Network (RNN) based state simulation and Reinforcement learning (RL) techniques to simulate future states and actions. A RNN state simulator and a RL action generator may be trained using patient data such as historical states and actions. The RL action generator may be optimized by applying the RNN state simulator to simulating future states and applying the RL action generator to generate recommended actions based on the simulated future states. This process may be iteratively performed until a computational convergence is reached by the RL action generator which may indicate that the RL action generator has been optimized. A patient state may be fed into the optimized RL action generator to generate an optimal recommended treatment action.

Abstract: A computer implemented method for processing a plurality of medical indication conditions on a computer that includes a processor communicatively coupled to a memory includes obtaining a plurality of predetermined indication conditions which relate to a plurality of parameters, and forming a plurality of conditional segments based on respective values of the plurality of parameters defined in the plurality of predetermined indication conditions. Each conditional segment of the plurality of conditional segments corresponds to a combination of different value ranges of respective parameters of the plurality of parameters. The plurality of predetermined indication conditions includes a measurement item, a reference standard, a time period, a measurement condition, and a measurement manner.