9 results about "Sample Measure" patented technology

This application provides a sample analysis system, which includes a sample measuring device and a control device. The control device is configured to: acquire sample information of each of a plurality of samples to be tested that are loaded onto the sample measuring device; mark one or more of the plurality of samples to be tested based on the information content of the sample information or in response to a first user operation on the sample information; and output a first control command after detecting that the sample measuring device has output test data of any marked sample on one or more test items; wherein the first control command is used to control one or more devices to output a first prompt message, the first prompt message being used to prompt that the marked sample to be tested has completed the test in the sample measuring device.

The present application provides a flow path cleaning method for an automatic sampler, which can balance the decrease of analysis throughput and the increase of cleaning solution consumption. In a flow path cleaning process (S12), when a cleaning solution is supplied by a cleaning solution supply mechanism to a flow path switched by a flow path switching mechanism among a first flow path including a nozzle for sucking a sample and a sample ring for holding the sample sucked from the nozzle, and a second flow path including a cleaning tank for cleaning at least an outer wall of the nozzle, a control device changes a flow rate of the cleaning solution supplied between measurement of a first measurement item of the sample and measurement of a second measurement item of the sample, based on first cleaning information indicating a cleaning mode corresponding to the first measurement item of the sample, and second cleaning information indicating a cleaning mode corresponding to the second measurement item of the sample measured after the first measurement item.

An automatic analysis device (100) is provided with an electrolyte measuring section (114) that performs measurement of an internal standard solution at least once before measurement of a potential of a sample, and in a case where measurement of the potential of the sample by the electrolyte measuring section (114) is continuously performed, the measurement operation of the internal standard solution before the measurement of the potential is changed depending on whether or not the sample measured the previous time is a high-concentration sample. Thus, an automatic analysis device and an automatic analysis method of a sample are provided, which can reduce carrying when performing electrolyte measurement, ensure measurement accuracy, and achieve improvement of the processing capacity of the entire device.

An objective of the present disclosure is to provide a technique for identifying normality level / abnormality level of sample processed by processing tool. The system according to the present disclosure comprises: a learner configured to learn a relationship between measurement data that describes a measurement result acquired by a first measuring tool and test data that describes a measurement result acquired by a second measuring tool which measures the sample after a manufacturing process for the sample is finished; and a processor that estimates, using the learner, a normality level or an abnormality level of the sample measured by the second measuring tool.

An objective of the present disclosure is to provide a technique for identifying normality level / abnormality level of sample processed by processing tool. The system according to the present disclosure comprises : a learner configured to learn a relationship between measurement data that describes a measurement result acquired by a first measuring tool and test data that describes a measurement result acquired by a second measuring tool which measures the sample after a manufacturing process for the sample is finished; and a processor that estimates, using the learner, a normality level or an abnormality level of the sample measured by the second measuring tool.

A sample measuring device reduces the frequency with which a user introduces a measurement aid into the sample measuring device is provided. A sample measuring method measures a sample using a container containing a measurement aid which is a solid. The sample measuring method includes loading a predetermined number of measurement aids into a container from a storage chamber in which a plurality of measurement aids are movably stored in a cartridge attached to a sample measuring device, dispensing the sample into the container, and measuring the sample in the container into which the measurement aid has been loaded.

A sample analysis system includes a plurality of measurement devices each configured to measure a sample to obtain a measurement result according to a measurement instruction including one or more measurement items, an identification information reader configured to read identification information of each sample of a plurality of samples measured by at least one of the plurality of measurement devices, and a computer including a storage device configured to store the measurement result. The computer is configured to perform operations for inter-instrument variability evaluation, the operations including querying the storage device to identify a set of the plurality of measurement results obtained from a plurality of target measurement devices, the set of the plurality of measurement results matching a condition for inter-instrument variability evaluation, and generating evaluation information for inter-instrument variability evaluation according to the set of the plurality of measurement results identified from the storage device.

A computer system stores a data set constituted with measurement data including measurement results of intensities of a plurality types of signals of particles contained in a sample measured using a flow cytometry, and a machine learning model configured to receive, as an input, a feature value of a first region generated by dividing an observation space using intensities of two or more types of signals as parameters based on a distribution feature of the measurement data in the observation space, and configured to output a probability of a class to which each coordinate of the observation space belongs. The computer system maps the measurement data into the observation space, divides the observation space into a plurality of the regions based on the distribution feature of the measurement data in the observation space, calculates a feature value of each region, inputs the feature value of each region into the machine learning model, and sets a gate based on the probability of the class to which each coordinate in the observation space belongs, which is output from the model.