Medical Information Retrieval with Weighting Critical Score for Acute Respiratory Infection (ARI) Desease Detection

Fika Hastarita Rachman ()

Technium, 2023, vol. 17, issue 1, 457-462

Abstract: Medical Information Retrieval (Med-IR )is part of computer science that discusses the search for a medical document. Medical Information Retrieval is needed by patients to know the initial prediction of the symptoms they are experiencing. ARI (Acute Respiratory Infection) is a disease that almost everyone has experienced which can cause death. This study uses a dataset of ARI sufferers and user queries that contain symptoms in text form. Furthermore, the query data is processed with the Med-IR application using Bi-Gram, TF-IDF as the feature extraction and Cosine Similarity as the similarity method, so that a return document is produced which is expected to be used as an early prediction of ARI in patients. The research also uses a critical disease wighting process, so that the results of the Med-IR are complemented by predictions of the severity level of the disease. From the results of research conducted at the Assyafi'u Sentosa Lengkong Clinic, Nganjuk, the best results were obtained for precision values ​​of 85.5% and 52.9% for recall values ​. The evaluation of disease severity with Mean Absolute Percentage Error (MAPE) getting a low score of 2,529%. Keyword : Medical Information Retrieval, ARI, Weighting critical disease, Bi-Gram, TF-IDF, Cosine Similarity.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:tec:techni:v:17:y:2023:i:1:p:457-462

DOI: 10.47577/technium.v17i.10124

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