Yapay Zekânın Maliyet Etkililiğini İnceleyen Yayınların Bibliyometrik, Kelime Bulutu ve Duygu Analizi

Year 2023, , 151 - 165, 30.04.2023

Gülçin Çalışkan , Songül Çınaroğlu

https://doi.org/10.17671/gazibtd.1197021

Cited By: 1

Abstract

Bu çalışma ile, bir karar destek sistemi olarak kullanılan yapay zekânın sağlık sorunlarının tespitinde ortaya koyduğu yöntemin mevcut yönteme göre maliyet etkililiğini tespit eden yayınların ayrıntılı olarak incelenmesi, konuyla ilgili küresel ilginin açığa çıkarılması, yayınların zaman içindeki eğilimlerinin ve hangi konuların daha çok araştırıldığının belirlenmesi amaçlanmıştır. Bununla birlikte bu çalışmanın diğer bir amacı bu yayınlarda en çok tekrar edilen kelimeleri vurgulamak ve yayınları duygu durumuna göre sınıflandırmaktır. Karar destek sistemi olarak kullanılan yapay zekânın sağladığı teşhis ya da tedavi yönteminin klasik teşhis ya da tedavi yöntemine göre maliyet etkililiği ile ilgili literatür Ağustos 2022'ye kadar Web of Science veri tabanında taranmıştır. Dışlama kriterleri uygulandıktan sonra literatür taramasında ulaşılan 24 yayın üzerinden bibliyometrik analiz, kelime bulutu ve duygu analizleri yapılmıştır. Araştırmada çok az sayıda çalışmaya ulaşıldığı ancak son yıllarda konuyla ilgili üretilen yayınların sayısında artış olduğu ve metinlerde en çok tekrar edilen anahtar kelimelerin sırasıyla yapay zekâ, maliyet etkililik, tarama ve makine öğrenimi olduğu tespit edilmiştir. Ayrıca hastalıkların teşhisinde yapay zekâ kullanılarak tanı koymanın klasik tanı koymaya göre maliyet etkililiğini tespit eden çalışmaların en fazla diş çürüğü, atriyal fibrilasyon ve diyabetik retinopati hastalıkları ile ilgili olduğu gözlenmiştir. Bununla birlikte kelime bulutunda en sık tekrar edilen kavramın “tarama” olduğu; duygu analizinde ise genel olarak pozitif duygunun daha ağır bastığı sonucuna ulaşılmıştır.

Keywords

yapay zeka, maliyet etkililik, diyabetik retinopati, atriyal fibrilasyon, diş çürüğü, tarama, bibliyometrik analiz

Bibliometric, Word Cloud and Sentiment Analysis of Publications Examining the Cost Effectiveness of Artificial Intelligence

Abstract

The aim of this study is to examine the publications that determine the cost-effectiveness of the current method compared to the method revealed by artificial intelligence, which is used as a decision support system in the determination of health problems, to reveal the global interest in the topic, to determine the trends of the publications over time and examine which topics are more researched. In addition, another aim of this study is to highlight the most frequently used words in these publications and to classify the publications according to their sentiment. The literature on the cost-effectiveness of the classical diagnosis or treatment method compared to the diagnosis or treatment method provided by artificial intelligence, which is used as a decision support system, was searched in the Web of Science database until August 2022. After the exclusion criteria was applied, bibliometric analysis, word cloud and sentiment analysis were performed on 24 publications reached during the review of the literature. It has been determined that there is a limited number of studies in the research, but there has been an increase in the number of publications on the topic in recent years, and the most frequently used keywords in the texts are artificial intelligence, cost-effectiveness, screening and machine learning, respectively. In addition, it was observed that the studies that determined the cost-effectiveness of diagnosing with artificial intelligence compared to diagnosing with classical method were mostly related to dental caries, atrial fibrillation and diabetic retinopathy diseases. Additionally, the most frequently used word in the word cloud is "screening"; In sentiment analysis, it was concluded that positive sentiment outweigh in general.

Keywords

artificial intelligence, cost-effectiveness, diabetic retinopathy, atrial fibrillation, dental caries, screening, bibliometric analysis

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