Noul Demonstrates AI-Driven On-Site Diagnostics Platform at MEDICA 2022

Noul Co., Ltd. (Gyeonggi-do, Korea) is demonstrating the world’s first integrated device featuring fully-automated sample preparation and AI-based diagnosis at the 2022 edition of MEDICA being held from 14 to 17 November in Düsseldorf, Germany.

At MEDICA 2022, Noul is demonstrating miLab, which is the world’s first all-in-one, fully-automated device which can process sample preparation and AI diagnostic in one workflow. miLab integrates cutting edge technologies from computer vision AI, bio, hardware and software engineering. From automated sample preparation to imaging and AI analysis, the miLab platform combines the gold standard in blood diagnostics into a fully automated benchtop platform. Combined with embedded AI and the company’s patented Next Generation Staining and Immunostaining (NGSI) cartridges, miLab provides an accurate analysis in 20 minutes using just 5 uL of blood. NGSI, the patented solid-based staining technology can replace the current liquid-based sample preparation methods and possess the potential to expand applicabilities to other diagnostic areas. NGSI technology eliminates the liquid usage in the sample staining process and can complete it in only a few minutes using a single step stamping method.

miLab provides superior accuracy compared to the competing technologies by combining multi-focus imaging and the state-of-the-art AI algorithm. The company’s AI can perfectly replicate the diagnosis of an expert microscopist without the errors and deviations. miLab’s AI algorithm analyzes multi-layered digital images of smeared blood cells to achieve 99%+ specificity in order to classify and detect parasite-infected cells. Among Noul’s offerings is the miLab Malaria which detects different stages of Plasmodium Falciparum and Plasmodium Vivax species and the miLab BCM which provides a morphology-based white blood cell (WBC) differential and cell count estimations, allowing decentralized health facilities to perform a WBC differential count and CBC estimation.

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