Abstract:
A patient condition prediction apparatus includes: an acquisition unit that obtains patient data, which are information about a patient; a selection unit that selects one predictive model from a plurality of predictive models for predicting a change in a patient condition that is a condition of the patient, on the basis of the patient data; and a prediction unit that predicts a change in the patient condition in the future by using the one predictive model. This makes it possible to predict a change in the patient condition by using an appropriate predictive model.
Abstract:
A medical facility evaluation apparatus includes: an acquisition unit that obtains a quantitatively measured evaluation information about a medical facility that is a candidate of a transfer destination of a patient; and a calculation unit that calculates a score indicating goodness of fit of the medical facility as the transfer destination with respect to the patient, on the basis of the evaluation information. According to this medical facility evaluation apparatus, scoring based on the quantitatively measured evaluation information makes it possible to find a medical facility with high goodness of fit as a transfer destination of a patient.
Abstract:
This medical information processing system is provided with: an operation policy input unit which receives a selection of an operation policy defining a plurality of operation policies which can be taken by a hospital as a whole; a model learning unit which refers to a database being managed so as to be accessible in the hospital, and generates, for each selectable operation policy, a maximization model of each operation policy with respect to an environmental change of the hospital; and a behavior optimization unit which, using the maximization model of the operation policy selected by the operation policy input unit, generates decision assistance information for a healthcare worker with respect to each patient that maximizes the overall efficiency of the hospital in accordance with the environmental change of the hospital.
Abstract:
A first prediction unit 81 predicts a transfer destination of a target patient, based on inputted information on the target patient and a first prediction model for prediction of a transfer destination of a patient. A second prediction unit 82 predicts a treatment completion period of the target patient, based on information on the target patient and a second prediction model for prediction of a treatment completion period of a patient. An acquisition unit 83 acquires facility information including an operation status of each facility. A determination unit 84 determines a facility that satisfies a requirement of a transfer destination from among the facilities, based on the facility information that has been acquired and the transfer destination and the treatment completion period that have been predicted. An output unit 85 outputs a result determined by the determination unit 84.
Abstract:
A packet transfer system includes a packet transfer unit (1) that transfers a packet between a first route and a second route, an electric buffer (2) that electrically stores and transfers the packet between the packet transfer unit (1) and the second route, and a power control unit (3) that controls power of the electric buffer (2) in accordance with traffic flowing through the electric buffer (2). It is thereby possible to provide a packet transfer system, a control device, a control method, and a non-transitory computer-readable medium storing a control program capable of achieving lower energy consumption.
Abstract:
An information processing device 100 of the present disclosure includes a data acquisition unit 121 and a data selection unit 122. The data acquisition unit 121 acquires biological data measured from a person whose state related to agitation is to be determined, and a determination result of the state by a determiner with respect to the person. The data selection unit 122 selects learning data from the biological data on the basis of a skill value and the determination result. The skill value represents the ability of determining the state and is set for the determiner. Selection of the learning data is optimized by the data selection unit 122 of the present disclosure.
Abstract:
In order to achieve an object to determine, with high accuracy, that a target is in a specific state, a state determination apparatus includes: a calculation section that calculates, on the basis of data obtained from the target, a score indicative of a degree to which the target is in the specific state; a decision section that decides a threshold on the basis of the data; and a determination section that determines, by comparing the score and the threshold, whether the target is in the specific state.
Abstract:
A disease risk prediction device 80 includes a prediction unit 81 and a prediction result output unit 82. The prediction unit 81 predicts a development risk of an infectious disease using a prediction model for predicting a development status of the infectious disease, the prediction model being learned based on electronic data of a patient. The prediction result output unit 82 outputs the predicted development risk.
Abstract:
A data management system is provided with: a storage unit for storing examination information including at least an examination item, an examination location, a consultation location, and a required examination time, the examination item including examination names of a plurality of examinations; an acquisition unit for acquiring patient information relating to severity and an identifier for identifying the patient to be examined; a calculation unit for calculating, in accordance with the patient, the necessary travel time for traveling from the examination location or consultation location at which a completed examination or consultation was performed to the next examination location or consultation location at which the next examination or consultation subsequent to the examination or consultation is to be performed, based on the patient information and the examination information; and a generating unit for generating a patient examination schedule based on the examination information, the patient information, and the travel time.
Abstract:
A medical information processing system comprises: an input unit that receives input of electronic chart information for a patient being treated; a machine learning unit that refers to an electronic chart information group for each patient, the information group being obtained on the basis of an inpatient of an acute care facility, and performs machine learning about the discharge destination, from the acute care facility, of each patient; and a discharge-destination prediction unit that predicts the discharge destination of the patient being treated from the received electronic chart information of the patient being treated, on the basis of the learning results obtained from the machine learning unit.