An artificial intelligence‐assisted diagnostic platform for rapid near‐patient hematology. Issue 10 (2nd August 2021)

• Record Type: Journal Article
• Authors: Bachar, Neta; Benbassat, Dana; Brailovsky, David; Eshel, Yochay; Glück, Dan; Levner, Daniel; Levy, Sarah; Pecker, Sharon; Yurkovsky, Evgeny; Zait, Amir; Sever, Cordelia; Kratz, Alexander; Brugnara, Carlo
• Is Part Of: American journal of hematology. Volume 96:Issue 10(2021)
• Page Start: 1264
• Page End: 1274
• Publication Date: 2021-08-02
• Subjects: Hematology -- Periodicals; 616.15
• DOI: 10.1002/ajh.26295
• Languages: English
• ISSNs: 0361-8609

Abstract

Abstract: Hematology analyzers capable of performing complete blood count (CBC) have lagged in their prevalence at the point‐of‐care. Sight OLO (Sight Diagnostics, Israel) is a novel hematological platform which provides a 19‐parameter, five‐part differential CBC, and is designed to address the limitations in current point‐of‐care hematology analyzers using recent advances in artificial intelligence (AI) and computer vision. Accuracy, repeatability, and flagging capabilities of OLO were compared with the Sysmex XN‐Series System (Sysmex, Japan). Matrix studies compared performance using venous, capillary and direct‐from‐fingerprick blood samples. Regression analysis shows strong concordance between OLO and the Sysmex XN, demonstrating that OLO performs with high accuracy for all CBC parameters. High repeatability and reproducibility were demonstrated for most of the testing parameters. The analytical performance of the OLO hematology analyzer was validated in a multicenter clinical laboratory setting, demonstrating its accuracy and comparability to clinical laboratory‐based hematology analyzers. Furthermore, the study demonstrated the validity of CBC analysis of samples collected directly from fingerpricks.