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In vivo confocal microscopy morphometric analysis of corneal subbasal nerve plexus in dry eye disease using newly developed fully automated system
摘要： Purpose To evaluate in vivo confocal microscopy (IVCM) features of corneal subbasal nerve plexus (SNP) in the setting of dry eye disease (DED) using fully automated software BACCMetrics,^ and to further investigate its diagnostic performance in discriminating DED patients. Methods IVCM exams of SNP in DED patients and matched control subjects were performed using Heidelberg Retina Tomograph with the Rostock Cornea Module. The following parameters were obtained with ACCMetrics: corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), corneal nerve fiber length (CNFL), corneal nerve total branch density (CTBD), corneal nerve fiber area (CNFA), corneal nerve fiber width (CNFW), and corneal nerve fractal dimension (CNFrD). The Mann–Whitney U test was used to compare variables. Receiver operating characteristic curves with calculations of the area under the curve (AUC) were used to describe the accuracy of IVCM parameters for discriminating DED patients from controls. Results Thirty-nine DED patients and 30 control subjects were included. Significantly, lower values of CNFD, CNBD, and CNFL and higher value of CNFW were found in DED patients compared to controls (respectively, 20.5 ± 8.7 vs 25.4 ± 6.7 n/ mm2; 25.6 ± 20.1 vs 37.6 ± 21.5 n/mm2; 12.6 ± 4.4 vs 14.5 ± 2.9 mm/mm2; 0.021 ± 0.001 vs 0.019 ± 0.001 mm/mm2; always p < 0.024). CNFW value had the highest diagnostic power in discriminating DED patients (AUC = 0.828). When the diagnosis of DED was made based on either CNFW or CNBD, the sensitivity was 97.4% and the specificity 46.7%. Conclusions The software ACCMetrics was able to rapidly detect SNP alterations occurring in the setting of DED and showed good diagnostic performance in discriminating DED patients.
关键词： Dry eye,Sub-basal nerve plexus,Automated analysis,ACCMetrics,In vivo confocal microscopy
更新于2025-09-23 15:22:29
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Implementation and Validation of an Automated Flow Cytometry Analysis Pipeline for Human Immune Profiling
摘要： Automated reagent preparation, sample processing, and data acquisition have increased the rate at which flow cytometry data can be generated. Furthermore, advances in technology and flow cytometry instrumentation continually increase the complexity and dimensionality of this data. Together, this leads to increased pressure on manual data analysis, which has inherent limitations including subjectivity of the analyst and the length of time needed for data processing. These issues can create bottlenecks in the data processing workflow and potentially compromise data quality. To address these issues, as well as the challenges associated with manual gating in a high-volume human immune profiling laboratory, we sought to implement an automated analysis pipeline. In this report, we discuss considerations for selecting an automated analysis method, the process of implementing an automated pipeline, and detail our successful incorporation of an automated gating strategy with flowDensity into our analysis workflow. This validated pipeline augments our laboratory’s ability to provide rapid high-throughput immune profiling for patients participating in cancer immunotherapy clinical trials.
关键词： cancer,automated gating,immunotherapy,automated analysis,immune profiling,T cells,flowDensity
更新于2025-09-04 15:30:14
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A Hierarchical Multi-Classifier System for Automated Analysis of Delayered IC Images
摘要： A robust and accurate machine learning based hierarchical multi-classifier system is proposed to automate the retrieval of interconnection information from delayered Integrated Circuits (IC) images. The proposed system replaces labor-intensive manual annotation process and provides an effective approach for automated analysis of state-of-the-art deep sub-micron IC chips.
关键词： machine learning,delayered IC images,hierarchical multi-classifier system,automated analysis
更新于2025-09-04 15:30:14