Medical documents contain valuable information about medication and symptoms, which help in improving health care. Recently, large volumes of medical documents are generated by electronic health record systems. These medical documents are unstructured or semi-structured from which extraction of useful information is a difficult task. Application of document clustering techniques is an efficient way for navigation and summarization of documents and very important for many natural language technologies [1]. Various partitional and agglomerative clustering techniques are applied in order to cluster the medical documents for grouping them into meaningful clusters
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Application of Clustering Algorithms to Group Medical Documents
Semantic Scholar · Medicine · 2019
Abstract
Medical documents contain valuable information about medication and symptoms, which help in improving health care. Recently, large volumes of medical documents are generated by electronic health record systems. These medical documents are unstructured or semi-structured from which extraction of useful information is a difficult task. Application of document clustering techniques is an efficient way for navigation and summarization of documents and very important for many natural language technologies [1]. Various partitional and agglomerative clustering techniques are applied in order to cluster the medical documents for grouping them into meaningful clusters