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STMicroelectronics Pte
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Chrontrol
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Beckhoff Automation GmbH Co KG
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IEEE Access
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International Federation of Clinical Chemistry and Laboratory Medicine
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Verlag GmbH
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Chrontrol
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Guangzhi Corporation
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MyoLearn
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Image Search Results
Journal: Journal of Clinical Laboratory Analysis
Article Title: Application of Patient‐Based Real‐Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening
doi: 10.1002/jcla.25019
Figure Lengend Snippet: Flow chart of setting up and verification of the PBRTQC procedure. EWMA, exponentially weighted moving average; IQC, internal quality control; LIS, laboratory information system; MA, moving average; n , batch size; PBRTQC, patient‐based real‐time quality control; λ , weighting coefficient.
Article Snippet: In this light, the use of patient samples for the purpose of continuous quality control, also known as patient‐based
Techniques: Control
Journal: Journal of Clinical Laboratory Analysis
Article Title: Application of Patient‐Based Real‐Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening
doi: 10.1002/jcla.25019
Figure Lengend Snippet: The distribution trends of truncated daily data and IQC data using the z ‐score charts. Truncated daily detection data of β‐HCG and AFP calculated by the PBRTQC EWMA intelligent procedure are plotted with green solid lines, and different levels of IQC data are shown with different colors of triangles in the z ‐score charts. The truncated daily data of analytes (A) β‐HCG and (B) AFP and the corresponding IQC data are shown in the z ‐score charts. (C) The percentage of PBRTQC accumulation CV of five analytes; TEA was the allowable total error ± 30%.
Article Snippet: In this light, the use of patient samples for the purpose of continuous quality control, also known as patient‐based
Techniques:
Journal: Journal of Clinical Laboratory Analysis
Article Title: Application of Patient‐Based Real‐Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening
doi: 10.1002/jcla.25019
Figure Lengend Snippet: Early‐warning signal provided by the optimal PBRTQC EWMA procedure in the AI‐MA platform. Solid line with yellow color in the z ‐score charts represent the early‐warning signal. (A) One negative‐bias early‐warning signal of β‐HCG between June 11 and June 23, 2021. (B) One positive‐bias early‐warning signal of uE 3 between June 24 and July 1, 2021.
Article Snippet: In this light, the use of patient samples for the purpose of continuous quality control, also known as patient‐based
Techniques:
Journal: Journal of Clinical Laboratory Analysis
Article Title: Application of Patient‐Based Real‐Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening
doi: 10.1002/jcla.25019
Figure Lengend Snippet: Concentration distribution of collected daily data and the corresponding IQC data. The chart of concentration frequency distribution of (A) m‐β‐HCG and (B) uE 3 from daily data. The IQC concentration of (C) m‐β‐HCG and (D) uE 3 ; L1, L2, and L3 represented the three concentration levels of IQC; Lot.1 and Lot.2 represent the IQC lot number 39190 and 89400, respectively. The daily detected data of (E) m‐β‐HCG and (F) uE 3 were transformed into the z ‐score charts by the optimal PBRTQC EWMA procedure in the AI‐MA platform.
Article Snippet: In this light, the use of patient samples for the purpose of continuous quality control, also known as patient‐based
Techniques: Concentration Assay, Transformation Assay