Algorithms for Natural Language Processing and Mining in Patient Records

• Published in: International Conference on Computing, Communication, and Networking Technologies (Online) pp. 1 - 6
• Main Authors: Raghu, N, Chakraborty, Shreya, Chauhan, Aakriti
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24.06.2024
• Subjects: Accuracy; Accurate; Algorithms; Approximately; Approximation algorithms; Clinical; Companies; Data mining; Elements; Facts; Medical diagnostic imaging; Medical services; Natural language processing; Person; Ultimately
• ISSN: 2473-7674
• DOI: 10.1109/ICCCNT61001.2024.10725497

Herbal Language Processing (NLP) and Mining Algorithms are frequently used to research big collections of patient electronic fitness information (EHR) to acquire insights that could be beneficial to patient care. Mining algorithms can assist to automate the technique of reading huge amounts of patient facts and may provide useful facts from affected person facts that would in any other case be difficult to method. NLP is getting used to extract records from unstructured textual content in patient statistics, that may useful resource in determining sicknesses, symptoms, medicines, and chance elements. by using the usage of NLP and system studying algorithms, all the facts from affected person records may be efficiently and as it should be processed, resulting in study's findings which can assist improve healthcare. NLP and mining algorithms for affected person facts can assist to streamline disorder diagnosis, provide extra accurate records approximately clinical selections, and ultimately improve patient results.