PACKET CONTENT PREDICTION IN A TELEPATHOLOGY SESSION
Nicy Malanda-Sendo
PACKET CONTENT PREDICTION IN A TELEPATHOLOGY SESSION.
Rel. Guido Marchetto, Alessio Sacco. Politecnico di Torino, Master of science program in Computer Engineering, 2020
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Abstract
Telepathology refers to practicing pathology from a distance. Telecommunications technology is used for facilitating the transmission of pathology image-rich data between two distant locations for diagnosis, research and education purposes. In order to perform telepathology, a pathologist must choose the video images that need to be analyzed and then render a diagnosis. The use of television microscopy, which preceded telepathology, didn’t require a pathologist to have a virtual or physical hands-on involvement in choosing the microscopic fields-of-view to analyze and diagnose. Today, With the wide application of prediction, especially in the telemedicine field, the research of prediction algorithm and theory has made a great progress.
The goal of this thesis is to propose an approach that uses a machine learning (ML) method, Hidden Markov Model (HMM), to predict the packet content from the generated network traffic
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