Sysmex has filed a patent for a specimen analyzer that uses artificial intelligence algorithms to analyze data from measurement samples. The analyzer includes multiple sample preparation parts, an optical detection part, and an analysis unit. The analysis unit performs various analysis operations on the data obtained from the samples to analyze different measurement items related to the analyte in the specimen. GlobalData’s report on Sysmex gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Specimen analyzer with artificial intelligence algorithm for analyzing analytes
A recently filed patent (Publication Number: US20230314457A1) describes a specimen analyzer designed to analyze an analyte in a specimen. The analyzer includes a measurement unit with multiple sample preparation parts that prepare measurement samples using the specimen and reagents. It also has an optical detection part that obtains optical signals from the measurement samples. An analysis unit is responsible for analyzing the data obtained from the optical signals.
The analysis unit performs various analysis operations using an artificial intelligence algorithm. It analyzes a first measurement item by processing the data from the first optical signal through a first analysis operation. It also analyzes a second measurement item using either the first analysis operation or a second analysis operation that processes a representative value derived from the first data. Additionally, the analysis unit performs analysis on the second measurement sample through a third analysis operation using a representative value derived from the second data.
The patent also mentions that the specimen analyzer can execute parallel preparation of multiple first measurement samples corresponding to different specimens. It specifies that the analysis unit determines the representative value in the second analysis operation based on the magnitude of the second data. Furthermore, the first optical signal has regions corresponding to different analytes in the specimen, and the analysis unit specifies the representative value based on the data from each region.
The optical detection part of the specimen analyzer includes a light source, a flow cell, and a photodetector. It applies light to the flow cell and detects light generated from the analyte in the specimen as it flows through the cell. The first data and second data correspond to the optical signals obtained when the analyte passes through the application position of the light.
The analysis unit utilizes an artificial intelligence algorithm, specifically a deep learning algorithm, to analyze the data. The first sample preparation parts are designed to classify white blood cells in the specimen, specifically into neutrophils, lymphocytes, monocytes, and eosinophils. The analysis unit can classify cells as nucleated red blood cells and basophils through the first analysis operation and classify cells as neutrophils, lymphocytes, monocytes, and eosinophils through the second analysis operation.
Overall, this patent describes a specimen analyzer that utilizes an artificial intelligence algorithm to analyze measurement samples and obtain valuable information about the analyte in the specimen. The analyzer allows for parallel processing of multiple samples and provides detailed analysis of different measurement items.
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