A Natural Language Processing-Based Turkish Diagnosis Recommendation System

Özlem Özcan Kılıçsaymaz; Servet Badem

doi:10.54047/bibted.1227017

EN TR

A Natural Language Processing-Based Turkish Diagnosis Recommendation System

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.

Keywords

AI-based Recommendation System, Machine Learning, Deep Learning, Turkish Natural Language Processing, LSTM(Long Short Term Memory), Recurrent Neural Network (RNN), Healthcare Recommendation System

Project Number

ATE-21-MDA

Yapay Zeka Tabanlı Türkçe Dİl İşleme, Tanı Öneri Sistemi Projesi

Abstract

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.

Keywords

AI-based Recommendation System, Machine Learning, Deep Learning, Turkish Natural Language Processing, LSTM(Long Short Term Memory), Recurrent Neural Network (RNN), Healthcare Recommendation System

Supporting Institution

ACIBADEM TEKNOLOJİ

Project Number

ATE-21-MDA

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Details

Primary Language

English

Subjects

Artificial Intelligence

Journal Section

Short Report

Authors

Özlem Özcan Kılıçsaymaz ^*
0000-0002-7282-512X
Türkiye

Servet Badem
0000-0002-9883-3056
Türkiye

Publication Date

August 9, 2023

Submission Date

December 31, 2022

Acceptance Date

March 30, 2023

Published in Issue

Year 2023 Volume: 4 Number: 1

DOI

https://doi.org/10.54047/bibted.1227017

IZ

https://izlik.org/JA25DZ94AP

APA

Özcan Kılıçsaymaz, Ö., & Badem, S. (2023). A Natural Language Processing-Based Turkish Diagnosis Recommendation System. Bilgisayar Bilimleri Ve Teknolojileri Dergisi, 4(1), 8-18. https://doi.org/10.54047/bibted.1227017

AMA

1.Özcan Kılıçsaymaz Ö, Badem S. A Natural Language Processing-Based Turkish Diagnosis Recommendation System. BIBTED. 2023;4(1):8-18. doi:10.54047/bibted.1227017

Chicago

Özcan Kılıçsaymaz, Özlem, and Servet Badem. 2023. “A Natural Language Processing-Based Turkish Diagnosis Recommendation System”. Bilgisayar Bilimleri Ve Teknolojileri Dergisi 4 (1): 8-18. https://doi.org/10.54047/bibted.1227017.

EndNote

Özcan Kılıçsaymaz Ö, Badem S (August 1, 2023) A Natural Language Processing-Based Turkish Diagnosis Recommendation System. Bilgisayar Bilimleri ve Teknolojileri Dergisi 4 1 8–18.

IEEE

[1]Ö. Özcan Kılıçsaymaz and S. Badem, “A Natural Language Processing-Based Turkish Diagnosis Recommendation System”, BIBTED, vol. 4, no. 1, pp. 8–18, Aug. 2023, doi: 10.54047/bibted.1227017.

ISNAD

Özcan Kılıçsaymaz, Özlem - Badem, Servet. “A Natural Language Processing-Based Turkish Diagnosis Recommendation System”. Bilgisayar Bilimleri ve Teknolojileri Dergisi 4/1 (August 1, 2023): 8-18. https://doi.org/10.54047/bibted.1227017.

JAMA

1.Özcan Kılıçsaymaz Ö, Badem S. A Natural Language Processing-Based Turkish Diagnosis Recommendation System. BIBTED. 2023;4:8–18.

MLA

Özcan Kılıçsaymaz, Özlem, and Servet Badem. “A Natural Language Processing-Based Turkish Diagnosis Recommendation System”. Bilgisayar Bilimleri Ve Teknolojileri Dergisi, vol. 4, no. 1, Aug. 2023, pp. 8-18, doi:10.54047/bibted.1227017.

Vancouver

1.Özlem Özcan Kılıçsaymaz, Servet Badem. A Natural Language Processing-Based Turkish Diagnosis Recommendation System. BIBTED. 2023 Aug. 1;4(1):8-18. doi:10.54047/bibted.1227017

A Natural Language Processing-Based Turkish Diagnosis Recommendation System

Abstract

Keywords

Project Number

Yapay Zeka Tabanlı Türkçe Dİl İşleme, Tanı Öneri Sistemi Projesi

Abstract

Keywords

Supporting Institution

Project Number

References

Details

Primary Language

Subjects

Journal Section

Authors

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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