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Publications

Digital Dermatopathology Implementation, Validation, and Cost Analysis in a Private Practice Setting

May 10, 2023
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5 Scanners for $100k: How to Utilize 5 Scanners in 5 Different Applications

In honor of our fifth anniversary and our ongoing commitment to democratizing access to digital pathology worldwide, we will be offering the biggest promotion in our company’s history
February 9, 2023
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Identification of Novel Biomarkers and Candidate Drug in Ovarian Cancer

In this work, a team conducts an investigation of the expression of the CREB1 gene in ovarian cancer by deeply excavating the gene information in multiple databases and the mechanism.
April 28, 2021
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The Pathologist: April 2021 “Picture Perfect Pathology”

Featured in April 2021’s edition of The Pathologist, various images scanned using a MoticEasyScan Pro were included in the “Picture Perfect Pathology,” editorial.
April 16, 2021
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Multi-Lens Arrays (MLA)-Assisted Photothermal Effects for Enhanced Fractional Cancer Treatment: Computational and Experimental Validations

In this work, a team conducts an investigation to experimentally demonstrate the therapeutic benefits of MLA-assisted fractional PTT on colorectal cancer, in comparison to flat fiber-based PTT.
April 8, 2021
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Motic Easy Scan Event Indoor Conference

The Future of Pathology is Digital

Published in Pathology – Research and Practice, this article evaluates the current state of digital pathology for clinical, research, and education use and looks forward to future challenges and developments.
February 15, 2021
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Tissue Factor Pathway Inhibitor is Required for Cerebrovascular Development in Mice

In this work, a team observed the interplay between TFPI and FV in regulating hemostasis and vascular development during embryogenesis.
January 12, 2021
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Validation of Telecytology for Rapid On-Site Evaluations at Cleveland Clinic

In this study, the team compared remote readouts done via the FS-Live system against on-record diagnoses for 120 previously diagnosed adequacy specimens.
December 9, 2020
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Evaluation of an Automated Microscope Using Machine Learning for the Detection of Malaria in Travelers Returned to the UK

In this work, a team evaluated EasyScan GO to determine if it could detect, quantitate, and identify malaria parasites present in Giemsa-stained blood lms with consistency and accuracy compared to trained microscopists.
November 23, 2020
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Multi-centric Field Evaluation Of A Digital Malaria Microscopy Device Based On Machine-Learning: EasyScan GO – A Preliminary Analysis

In this work, a team assessed the performance of the EasyScan Go, a microscopy device employing machine learning-based image analysis to detect malaria parasites.
November 23, 2020
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