Abstract
A REVIEW ON TEXT DATA MINING OF CARE LIFE LOG USING KEY GRAPH
*Devanshi Nayak and Dr. Avinash Sharma
ABSTRACT
Data Mining is a method that requires analyzing and exploring large blocks of data to glean meaningful trends and patterns. In today?s period, every person on earth relies on allopathic treatments and medicines. Data mining techniques can be applied to medical databases that have a vast scope of opportunity for textual as well as visual data. Care Life Log is used to integrate and analyze the level of care required. There are five levels of care, with Level 1 vocabulary including recreation, toilet, morning, afternoon, etc. The level of care gradually increases from Level 1 to Level 5, which has vocabulary that includes tube, danger, treatment, removal, and discovery. The higher the level, the worse the health condition and therefore the greater care required. These levels allow for a clear analysis of a patient?s condition. This analysis has led to an improvement in Quality of Life as well as a decrease in mismatches between the level of care required for patients and the level of care given by care takers. The qualitative analysis result of in-patient nursing records used a text data mining technique to achieve the initial goal: a visual record of such information. The analysis discovered vocabularies relating to proper treatment methods and concisely summarized their extracts from in-patient nursing records. Important vocabularies that characterize each nursing record were also revealed. The results of this research will contribute to nursing work evaluation and education. This research used a text data mining technique to extract useful information from nursing records within Electronic Medical Records.
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