Version 1
: Received: 17 February 2024 / Approved: 18 February 2024 / Online: 19 February 2024 (11:35:26 CET)
How to cite:
Budaraju, R.; Jammalamadaka, S.K.R. Finding Negative Associations from Medical Data Streams Based on Frequent and Regular Patterns. Preprints2024, 2024020946. https://doi.org/10.20944/preprints202402.0946.v1
Budaraju, R.; Jammalamadaka, S.K.R. Finding Negative Associations from Medical Data Streams Based on Frequent and Regular Patterns. Preprints 2024, 2024020946. https://doi.org/10.20944/preprints202402.0946.v1
Budaraju, R.; Jammalamadaka, S.K.R. Finding Negative Associations from Medical Data Streams Based on Frequent and Regular Patterns. Preprints2024, 2024020946. https://doi.org/10.20944/preprints202402.0946.v1
APA Style
Budaraju, R., & Jammalamadaka, S.K.R. (2024). Finding Negative Associations from Medical Data Streams Based on Frequent and Regular Patterns. Preprints. https://doi.org/10.20944/preprints202402.0946.v1
Chicago/Turabian Style
Budaraju, R. and Sastry Kodanda Rama Jammalamadaka. 2024 "Finding Negative Associations from Medical Data Streams Based on Frequent and Regular Patterns" Preprints. https://doi.org/10.20944/preprints202402.0946.v1
Abstract
Medical data flows in streams as the data related to clinical tests and administered drugs by the doctors flows continuously. The doctors must be immediately alerted if negative associations are found among the drugs they prescribe. Data streams are to be processed in single scans as it is not possible to re-scan the data for any iterative processing. To detect negative drug connections, regular and frequent drug patterns must be processed. Negative correlations between disease-curing medications might create adverse responses that kill patients. This paper proposes an algorithm that finds the negative associations among regular and frequent patterns mined from medical data streams. The negative associations mined are the most effective and reduce the negative associations, which are more critical by 50%.
Keywords
Data streams; Negative associations; Adverse effects; side reactions; Frequent and Regular patterns
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
