According to the World Malaria Report, nearly 240 million cases of malaria are being reported annually. This highlights the prevalence of the disease particularly in third-world countries. The need for systematic diagnosis paved the way for the automated diagnosis landscape, wherein slide images infested with parasites were analyzed for the presence of the Plasmodium parasite. In this session, we deal with using Microsoft's Azure Custom Vision Service for detecting the presence of the parasite in slide images and predicting malarial infestation. We will also learn how to integrate the Custom Vision Application with Power Apps to create a resilient application to accept slide images and predict the likelihood of malarial infestation.
Sanya is a college sophomore at Birla Institute of Technology, India. She is very interested in the fields of Data Science, AI/ML/DL, and Cloud Computing, and shall be working as a UG Research Intern at the University of Texas at Austin in the Summer of 2022. She is a published author and a technical content writer and strongly believes in community culture for overall development. She is a Gold Microsoft Learn Student Ambassador, an Azure Hero, and the Editorial and Review Community Lead for MLSA venture Voice of Code.
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