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Development and validation of an app-based cell counter for use in the clinical laboratory setting
Author(s) -
Alexander C Thurman,
Jessica L. Davis,
Max Jan,
Charles E. McCulloch,
Benjamin Buelow
Publication year - 2015
Publication title -
journal of pathology informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.009
H-Index - 17
ISSN - 2153-3539
DOI - 10.4103/2153-3539.150252
Subject(s) - touchscreen , computer science , peripheral blood , interface (matter) , outlier , cell counting , pattern recognition (psychology) , medicine , cell , artificial intelligence , human–computer interaction , biology , immunology , genetics , bubble , maximum bubble pressure method , parallel computing , cell cycle
For decades cellular differentials have been generated exclusively on analog tabletop cell counters. With the advent of tablet computers, digital cell counters - in the form of mobile applications ("apps") - now represent an alternative to analog devices. However, app-based counters have not been widely adopted by clinical laboratories, perhaps owing to a presumed decrease in count accuracy related to the lack of tactile feedback inherent in a touchscreen interface. We herein provide the first systematic evidence that digital cell counters function similarly to standard tabletop units. Methods: We developed an app-based cell counter optimized for use in the clinical laboratory setting. Paired counts of 188 peripheral blood smears and 62 bone marrow aspirate smears were performed using our app-based counter and a standard analog device. Differences between paired data sets were analyzed using the correlation coefficient, Student′s t-test for paired samples and Bland-Altman plots. Results: All counts showed excellent agreement across all users and touch screen devices. With the exception of peripheral blood basophils (r = 0.684), differentials generated for the measured cell categories within the paired data sets were highly correlated (all r ≥ 0.899). Results of paired t-tests did not reach statistical significance for any cell type (all P > 0.05), and Bland-Altman plots showed a narrow spread of the difference about the mean without evidence of significant outliers. Conclusions: Our analysis suggests that no systematic differences exist between cellular differentials obtained via app-based or tabletop counters and that agreement between these two methods is excellent

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