Neel Kanwal
Dilated Convolution Networks for Classification of ICD-9 based Clinical Summaries.
Rel. Maurizio Morisio, Giuseppe Rizzo. Politecnico di Torino, Corso di laurea magistrale in Communications And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni), 2020
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Abstract
Deployment of Artificial Intelligence for understanding clinical notes in the healthcare sector is a crucial step to extract meaningful phrases based on diseases. Electronic Health Records (EHR) are stored in the health care system in an unstructured and event associated way. Public clinical records can be used for billing, monitoring and insurance purpose. These clinical notes contain abbreviations, acronyms, and a non-uniform dictionary. Various Machine learning models are used with different approaches to understand these notes, these models are evaluated in various criteria based on datasets. These techniques differed mainly in pre-processing and code assignments as well as architecture for reading long medical documents.
In this thesis work, we propose a layered model of Convolution Neural Networks with pre-trained embeddings
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