Hilab System Device in an Oncological Hospital: A New Clinical Approach for Point of Care CBC Test, Supported by the Internet of Things and Machine Learning.

The complete blood count (CBC) is a highly requested test that is generally restricted to centralized laboratories, which are limited by high cost, being maintenance-demanding, and requiring costly equipment. The Hilab System (HS) is a small, handheld hematological platform that uses microscopy and chromatography techniques, combined with machine learning (ML) and artificial intelligence (AI), to perform a CBC test. This platform uses ML and AI techniques to add higher accuracy and reliability to the results besides allowing for faster reporting.

Enhancing a SARS-CoV-2 nucleocapsid antigen test sensitivity with cost efficient strategy through a cotton intermembrane insertion.

Lateral flow antigen tests have been widely used in the Covid-19 pandemic, allowing faster diagnostic test results and preventing further viral spread through isolation of infected individuals. Accomplishment of this screening must be performed with tests that show satisfactory sensitivity in order to successfully detect the target protein and avoid false negatives. The aim of this study was to create a lateral flow test that could detect SARS-CoV-2 nucleocapsid protein in low concentrations that were comparable to the limits of detection claimed by existing tests from the market.

Hilab system, a new point-of-care hematology analyzer supported by the Internet of Things and Artificial Intelligence.

The complete blood count (CBC) is one of the most requested tests by physicians. CBC tests, most realized in conventional hematological analyzers, are restricted to centralized laboratories due to frequent maintenance, large devices, and expensive costs required. On the other hand, most handheld CBC devices commercially available show high prices and are not liable to calibration or control procedures, which results in poor quality compared to standard hematology instruments.