Abstract: A clinical decision support device of an embodiment includes processing circuitry. The processing circuitry acquires at least one of attribute information of a patient and first parameters regarding a first preference category for the patient. The processing circuitry estimates second parameters of the patient with respect to a second preference category on the basis of at least one of the attribute information and the first preference category. The processing circuitry determines preferable selections of the patient with respect to a predetermined preference category on the basis of the second parameters. The processing circuitry displays the preferable selections and the second parameters in association with each other.

Abstract: A medical information processing apparatus according to an embodiment includes a processing circuitry. The processing circuitry acquires operation information of a medical worker for medical treatment information of a target patient or operation information of a medical worker for medical treatment information of a similar patient who is similar to the target patient. Based on the operation information, the processing circuitry calculates the concordance rate between a period for which the medical treatment information of the target patient or the medical treatment information of the similar patient is referred to and the period for which the medical treatment information of the target patient is displayed. The processing circuitry performs display of information about the concordance rate.

Abstract: A consensus building support system according to an embodiment includes processing circuitry. The processing circuitry stores a database that stores a state of a first user and actions by the first user and a second user. The processing circuitry calculates a first state assessment index representing a first user's assessment of the state based on a first user's state and an action relating to the first user, and calculates a second state assessment index representing a second user's assessment of the state based on the first user's state and an action relating to the second user. The processing circuitry display a first state assessment index and/or a second state assessment index on a display.

Abstract: An information processing device of an embodiment includes processing circuitry. The processing circuitry is configured to acquire a global model based on data sets regarding a plurality of cohorts, acquire a local model based on a first data set regarding at least one first cohort among the plurality of cohorts, calculate a weight based on a first data distribution with respect to the first data set and a second data distribution with respect to a second data set regarding the plurality of cohorts, and calculate an index value regarding the global model on the basis of the first data set and the weight.

Abstract: A medical information processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires a first diagnostic result by a clinical decision support system before learning of first data, a second diagnostic result by the clinical decision support system after learning of the first data, a diagnostic result by a doctor, and the first data. The processing circuitry extracts an example that is subjected to an influence of updating of the clinical decision support system by a prescribed criterion or more as an example to be presented. The processing circuitry outputs the example to be presented in association with a diagnosis influence degree indicator indicating a degree of an influence that the clinical decision support system exerts on diagnosis by the doctor.

Abstract: A learning assistance apparatus according to an embodiment includes processing circuitry. Based on a knowledge base in which a condition of medical data as an index for medical judgment and medical knowledge derived from the condition are associated with each other, and a model designed to derive a medical inference result from a condition of medical data concerning a subject in response to input of the medical data, the processing circuitry compares the medical data condition related to the derivation of the medical knowledge and the medical data condition related to the derivation of the inference result, for each item of the medical data, and outputs a result of the comparison.

Abstract: An apparatus for determining a contour of a treatment region in a patient includes a computer processor to receive input regarding a contour of at least one organ-at-risk (OAR) adjacent to the treatment region; receive input regarding an initial contour of the treatment region; predict a radiation toxicity to the at least one OAR based on the contour of the at least one OAR, the initial contour of the treatment region, and a radiation treatment regimen; determine whether the predicted radiation toxicity exceeds a threshold; and determine a contour of the treatment region by iteratively modifying the initial contour of the treatment region, and any subsequent modified contours of the treatment region, until a stopping condition is satisfied. The stopping condition can be a preselected number of iterations or that the predicted radiation toxicity using the contour in place of the initial contour is first calculated is below said threshold.

Abstract: An apparatus for determining a contour of a treatment region in a patient includes a computer processor to receive input regarding a contour of at least one organ-at-risk (OAR) adjacent to the treatment region; receive input regarding an initial contour of the treatment region; predict a radiation toxicity to the at least one OAR based on the contour of the at least one OAR, the initial contour of the treatment region, and a radiation treatment regimen; determine whether the predicted radiation toxicity exceeds a threshold; and determine a contour of the treatment region by iteratively modifying the initial contour of the treatment region, and any subsequent modified contours of the treatment region, until a stopping condition is satisfied. The stopping condition can be a preselected number of iterations or that the predicted radiation toxicity using the contour in place of the initial contour is first calculated is below said threshold.

Abstract: A server includes a distribution difference calculator and a determining unit. The distribution difference calculator calculates difference information between a first distribution of features calculated from operating data of terminal devices of a first machine type and a second distribution of features calculated from operating data of terminal devices of a second machine type. The determining unit determines whether a model is applicable to the terminal devices of the first machine type to predict occurrence possibility of a failure in each terminal device of the first machine type on basis of the difference information wherein the model is generated on basis of operating data of the terminal devices of the second machine type and is configured to predict occurrence possibility of a failure in each terminal device of the second machine type on basis of each of the features calculated from the operating data thereof.

Abstract: A data preserving apparatus includes: a generator generating scenarios that represent presence or absence of occurrence of a failure, presence or absence of a failure symptom, a time point of occurrence of a failure, and a time point of occurrence of a failure symptom; an evaluator calculating the amount of data loss in the case of occurrence of a failure for the scenario based on first and second backup intervals before and after occurrence of a failure symptom; an backup interval evaluator calculating a number of backups performed until earlier one of a time point of occurrence of a failure and a time point after a predetermined time period; a cost evaluator calculating a cost evaluation values for the scenarios based on the amount of data loss and the number of backups; and a calculator calculating the first and second backup intervals based on cost evaluation values for scenarios.

Abstract: In a model parameter calculation device, the comparator compares a first evaluation value calculated from a first model and operating data on a terminal device with a second evaluation value calculated from a second model and the operating data. The requester transmits an inspection request to inspect the terminal device to the terminal device or a management device thereof in accordance with a comparative relation between the first evaluation value and the second evaluation value. The parameter determiner determines a third parameter included in a third model in accordance with a model reference of a predefined model type, on basis of an inspection result indicating an operating status of the terminal device and the operating data of the terminal device, wherein the third model associates the third parameter with a third output variable regarding the occurrence possibility of the failure in the terminal device.

Abstract: A server includes a distribution difference calculator and a determining unit. The distribution difference calculator calculates difference information between a first distribution of features calculated from operating data of terminal devices of a first machine type and a second distribution of features calculated from operating data of terminal devices of a second machine type. The determining unit determines whether a model is applicable to the terminal devices of the first machine type to predict occurrence possibility of a failure in each terminal device of the first machine type on basis of the difference information wherein the model is generated on basis of operating data of the terminal devices of the second machine type and is configured to predict occurrence possibility of a failure in each terminal device of the second machine type on basis of each of the features calculated from the operating data thereof.

Abstract: According to one embodiment, a measurement unit periodically measures a usage status of a measurement target, and measures each test item of the measurement target at an arbitrary timing according to a test schedule. A first storage unit stores the usage status and a test result in time series. A second storage unit stores statistic information representing a relationship between the usage status and the test result. A probability calculation unit calculates a first evaluation value representing a load of the measurement target at a recent timing and a second evaluation value representing a load of the measurement target at the arbitrary timing, based on the usage status, and calculates a specific probability of each test item, based on the statistic information, the first evaluation value and the second evaluation value. A test schedule creation unit creates a new test schedule having selected test items, based on the specific probability.

Abstract: There is provided an analysis apparatus including: a first storage to store operation data on an electronic device; a second storage to store a span characteristic concerning a time span in which each of values of a plurality of explanatory variables is changed; an explanatory variable calculator to calculate the explanatory variables based on the operation data; a failure state information calculator to calculate failure state information for the electronic device based on the explanatory variables calculated by the explanatory variable calculator, and calculate, when the failure state information represents a risky state, an overall span concerning in what time span the failure state information is possibly to represent a safe state due to changes in the values of the explanatory variables; and a diagnosis unit to diagnose the electronic device based on the failure state information and the overall span characteristic.

Abstract: A data preserving apparatus includes: a generator generating scenarios that represent presence or absence of occurrence of a failure, presence or absence of a failure symptom, a time point of occurrence of a failure, and a time point of occurrence of a failure symptom; an evaluator calculating the amount of data loss in the case of occurrence of a failure for the scenario based on first and second backup intervals before and after occurrence of a failure symptom; an backup interval evaluator calculating a number of backups performed until earlier one of a time point of occurrence of a failure and a time point after a predetermined time period; a cost evaluator calculating a cost evaluation values for the scenarios based on the amount of data loss and the number of backups; and a calculator calculating the first and second backup intervals based on cost evaluation values for scenarios.

Abstract: A user evaluation apparatus includes a parameter determination module which determines parameters of a user evaluation model required to calculate a degree of usage influence so as to maximize a target function. The target function may be defined using weight values, measurement data, and a failure information counting result. The apparatus also includes a user evaluation module which calculates and displays the degree of usage influence using the measurement data and the parameters of the user evaluation model.

Abstract: A first module calculates a failure occurrence risk index of each data storage area address. A second module calculates a power saving index of each data storage area address. A third module calculates an access speed index per unit data volume necessary to access each data storage area address. A fourth module generates a distribution table that represents the failure occurrence risk index, the power saving index, and the access speed index for each candidate address, with respect to data to be distributed. A fifth module selects a candidate address in the distribution table such that the power saving index and the access speed index meet restricting conditions and the failure occurrence risk index is minimized, and distributes the data to the candidate address.

Abstract: According to one embodiment, an evaluating apparatus includes an operation data storage unit, a labeling unit, a learning unit, and an evaluating unit. The labeling unit applies a failure label, indicating that a product is broken down, to operation data of the product that is broken down within a designated period of time from the observation date of the operation data, while applies a non-failure label, indicating that the product is not broken down, to the operation data of the product that is not broken down within a designated period of time from the observation date of the operation data. The labeling unit applies neither the failure label nor the non-failure label to the operation data of the product, which is not certain that it is broken down or not within a designated period of time from the observation date of the operation data.

Abstract: A first module calculates a failure occurrence risk index of each data storage area address. A second module calculates a power saving index of each data storage area address. A third module calculates an access speed index per unit data volume necessary to access each data storage area address. A fourth module generates a distribution table that represents the failure occurrence risk index, the power saving index, and the access speed index for each candidate address, with respect to data to be distributed. A fifth module selects a candidate address in the distribution table such that the power saving index and the access speed index meet restricting conditions and the failure occurrence risk index is minimized, and distributes the data to the candidate address.

Abstract: A first module calculates a failure occurrence risk index of each data storage area address. A second module calculates a power saving index of each data storage area address. A third module calculates an access speed index per unit data volume necessary to access each data storage area address. A fourth module generates a distribution table that represents the failure occurrence risk index, the power saving index, and the access speed index for each candidate address, with respect to data to be distributed. A fifth module selects a candidate address in the distribution table such that the power saving index and the access speed index meet restricting conditions and the failure occurrence risk index is minimized, and distributes the data to the candidate address.