An analyzer configured to acquire a chromatogram or spectrum by performing a predetermined analysis of a sample and perform a qualitative or quantitative analysis of components contained in the sample. The analyzer includes: a peak detection unit configured, based on information regarding a plurality of target components that need to be checked whether contained in the sample or that need to be quantified, to detect a peak or peaks in the chromatogram or spectrum acquired by the predetermined analysis of the sample corresponding to one of the target components, configured to acquire peak information regarding each of the peak or peaks, and configured to obtain confidence information for each of the peak or peaks, the confidence information being an indicative value of certainty of detecting a peak; and a display processing unit configured to display on a display unit a list of at least a part of the target components.

A computer-implemented method for detecting at least one interference and/or at least one artefact in at least one chromatogram determined by at least one mass spectrometry device (110) is proposed. The chromatogram comprises a plurality of raw data points. The method comprises the following steps: a) retrieving the at least one chromatogram by at least one processing device (126); b) applying at least one peak fit modelling to the chromatogram by using the processing device (126); c) determining information about residuals of the raw data points by using the processing device (126); d) detecting the at least one interference and/or the at least one artefact by using the processing device (126) by comparing the determined information about the residuals with at least one pre-determined threshold, wherein, if the determined information about the residuals exceed the pre-determined threshold, the at least one interference and/or the at least one artefact is detected.

A training method includes: acquiring a pseudo noise waveform indicating an assumed noise; acquiring a pseudo peak waveform not including the pseudo noise; generating a pseudo signal waveform by adding the pseudo noise waveform and the pseudo peak waveform; and updating an estimation model based on the pseudo signal waveform, in which the acquiring the pseudo noise waveform includes: causing an analysis device to execute noise measurement generating the pseudo noise waveform a plurality of times; calculating a similarity degree of a plurality of pseudo noise waveforms generated by the noise measurement performed the plurality of times; and executing prescribed processing according to the similarity degree.

An analysis assistance device includes a chromatogram generator that generates a chromatogram using measurement data obtained from an analysis device, an area calculator that calculates an area percentage of each peak included in the chromatogram, a determiner that determines a separation state of each peak included in the chromatogram, and an analysis assistance information outputter that outputs analysis assistance information to a display. The analysis assistance information outputter includes a chromatogram outputter that outputs the chromatogram generated by the chromatogram generator to the display and also outputs information to display one peak in an identified manner when the one peak has an area percentage of not less than a predetermined threshold value, and the determiner determines that the one peak is an unseparated peak.

A first correlation equation is preliminarily determined from a chromatogram obtained by subjecting, to liquid chromatography, a first blood sample group which is known to contain HbA1c, and whose content ratio of HbF in total hemoglobin is known to be less than a predetermined content ratio, the first correlation equation being a correlation equation between an HbA1c peak value and a composite peak value including an HbA1a peak and an HbA1b peak. A composite peak value obtained by applying, to the first correlation equation, an HbA1c peak value of a chromatogram obtained by subjecting a measurement target blood sample to liquid chromatography is subtracted from a composite peak value including an HbA1a peak and an HbA1b peak in the blood sample, to calculate a modified HbF peak value. The modified HbF peak value is added to an HbF peak value of the blood sample, to correct the HbF peak value.

An analysis device produces learning data for training processing of an estimation model More specifically, the analysis device obtains a plurality of reference waveforms for a given type of device. In addition, the analysis device specifies information about a peak for each of the plurality of reference waveforms according to a criterion corresponding to the given type of device. The analysis device assigns the specified information about the peak to each of the plurality of reference waveforms.

The method according to the present invention includes: a training sample measurement process (S1, S2) in which, for a food product belonging to the same kind as a determination target, a plurality of training samples individually labeled with a known state of quality are subjected to a measurement using a chromatograph mass spectrometer under the same analysis condition; a training sample data collection process (S3, S4) in which an index value related to the magnitude of a peak observed on an extracted ion chromatogram obtained by the measurement is acquired for each training sample, and the index value of the peak at each retention time common to the training samples is extracted; and a discrimination model creation process (S5-S7) in which a supervised training is performed to create a discrimination model, using, as the training data, the index value of the peak at each retention time common to the training samples acquired for each of the labeled training samples. Measurement data for an unknown sample is inputted into a discriminator based on the discrimination model, to obtain a quality discrimination result.

An analysis assistance device includes an estimator that estimates distribution of measurement quality index data using a plurality of analysis condition data to be provided to an analysis device and a plurality of measurement data obtained in the analysis device based on the plurality of analysis condition data, a calculator that calculates the measurement quality index data from the measurement data obtained from the analysis device, and a comparison outputter that compares and outputs for display the measurement quality index data estimated by the estimator and the measurement quality index data calculated by the calculator.

A method for monitoring an analyzer including a liquid chromatography device (LC) having at least two liquid chromatography (LC) streams, the method including continuously monitoring one or more parameters in measurement data of samples in each of the at least two LC streams, the one or more parameters being independent of an analyte concentration of the respective sample, determining if the one or more monitored parameters show an expected behavior and triggering a response upon detection that the one or more monitored parameters deviate from the expected behavior.

An analysis assistance device includes an estimator that estimates a distribution of measurement quality indicator data by performing a regression analysis with use of a plurality of analysis condition data pieces supplied to an analysis device and a plurality of measurement data pieces obtained by the analysis device based on the plurality of analysis condition data pieces, and an analysis assistance information outputter that outputs a distribution of the measurement quality indicator data to a display device. The analysis condition data pieces include a first factor. The estimator estimates respective distributions of the measurement quality indicator data in a case in which the first factor is a first value and a case in which the first factor is a second value. The analysis assistance information outputter outputs the respective distributions to the display device.