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An artificial intelligence-assisted diagnostic platform for rapid near-patient hematology.


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.

SUBMITTER: Bachar N 

PROVIDER: S-EPMC9290600 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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An artificial intelligence-assisted diagnostic platform for rapid near-patient hematology.

Bachar Neta N   Benbassat Dana D   Brailovsky David D   Eshel Yochay Y   Glück Dan D   Levner Daniel D   Levy Sarah S   Pecker Sharon S   Yurkovsky Evgeny E   Zait Amir A   Sever Cordelia C   Kratz Alexander A   Brugnara Carlo C  

American journal of hematology 20210802 10


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  ...[more]

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