: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.

Introduction: Malaria is one of the most prevalent infectious diseases in sub-Saharan Africa, with 247 million cases reported worldwide in 2021 according to the World Health Organization. Optical microscopy remains the gold standard technique for malaria diagnosis, however, it requires expertise, is time-consuming and difficult to reproduce. Therefore, new diagnostic techniques based on digital image analysis using artificial intelligence tools can improve diagnosis and help automate it.

Operationalizing and automating Data Governance.

The ability to cross data from multiple sources represents a competitive advantage for organizations. Yet, the governance of the data lifecycle, from the data sources into valuable insights, is largely performed in an ad-hoc or manual manner. This is specifically concerning in scenarios where tens or hundreds of continuously evolving data sources produce semi-structured data.

Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review.

Malaria is an infectious disease caused by parasites of the genus spp. It is transmitted to humans by the bite of an infected female mosquito. It is the most common disease in resource-poor settings, with 241 million malaria cases reported in 2020 according to the World Health Organization.