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Journals / Bilgisayar Bilimleri ve Teknolojileri Dergisi / 2023 / Cilt: 4 Sayı: 1

A Natural Language Processing-Based Turkish Diagnosis Recommendation System

Yapay Zeka Tabanlı Türkçe Dİl İşleme, Tanı Öneri Sistemi Projesi

Servet BADEM
Özlem ÖZCAN KILIÇSAYMAZ
Pages
8–18
Publication Date
2023-08-09
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

As a result of the study, the diagnosis proposal for the patient's complaints was successfully predicted with the applied recurrent neural networks (RNN) model approach.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:MD-Advisor is the abbreviation of “medical doctor – advisor” which is an artificial intelligence-based recommendation system in healthcare.
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Key Findings & Data:Moreover, the health-based recommender system is a decision-making tool that makes recommendations for appropriate healthcare information to patients and clinicians.
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Conclusion & Impact:As a result of the study, the diagnosis proposal for the patient's complaints was successfully predicted with the applied recurrent neural networks (RNN) model approach.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:AI-based Recommendation System · Machine Learning · Deep Learning

Abstract

MD-Advisor is the abbreviation of “medical doctor – advisor” which is an artificial intelligence-based recommendation system in healthcare. Moreover, the health-based recommender system is a decision-making tool that makes recommendations for appropriate healthcare information to patients and clinicians. MD-Advisor project was developed in order to speed up the procedures that doctors follow when diagnosing patients and to present all possible conditions to the doctor in a short time. With this project, the processes of diagnosing the patient and then recommending the examination are completed very quickly. Thus, the patient is directly transferred to the treatment phase. Based on the data obtained from patient complaints which indicates the current health status of the patient; data preprocessing, labeling and deep learning modeling techniques are used. The diagnostic codes used as labels for the diagnosis recommendation were obtained as output from the Recurrent Neural Networks model. As a result of the study, the diagnosis proposal for the patient's complaints was successfully predicted with the applied recurrent neural networks (RNN) model approach.

Özet

MD-Advisor, sağlık hizmetlerinde yapay zeka tabanlı bir öneri sistemi olan “tıp doktoru – danışman” ifadesinin kısaltmasıdır. Ayrıca sağlık temelli öneri sistemi, hastalara ve klinisyenlere uygun sağlık hizmeti bilgileri için önerilerde bulunan bir karar alma aracıdır. MD-Advisor projesi, doktorların hastalara teşhis koyarken izledikleri prosedürleri hızlandırmak ve olası tüm durumları kısa sürede doktora sunmak amacıyla geliştirilmiştir. Bu proje ile hastaya teşhis konulması ve sonrasında tetkik önerilmesi süreçleri çok hızlı bir şekilde tamamlanmaktadır. Böylece hasta doğrudan tedavi aşamasına geçmektedir. Hastanın mevcut sağlık durumunu gösteren hasta şikayetlerinden elde edilen verilere dayanarak; veri ön işleme, etiketleme ve derin öğrenme modelleme teknikleri kullanılmaktadır. Teşhis önerisi için etiket olarak kullanılan teşhis kodları, Tekrarlayan Sinir Ağları modelinden çıktı olarak elde edildi. Çalışma sonucunda uygulanan tekrarlayan sinir ağları (RNN) modeli yaklaşımı ile hastanın şikayetlerine yönelik tanı önerisi başarılı bir şekilde tahmin edilmiştir.

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Cite This Article

BADEM, S., KILIÇSAYMAZ, Ö. Ö. (2023). A Natural Language Processing-Based Turkish Diagnosis Recommendation System. Bilgisayar Bilimleri ve Teknolojileri Dergisi, Cilt: 4 Sayı: 1, 8–18. https://ajindex.com/articles/957111

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