Bibliometric Analysis of Artificial Intelligence Research in the Healthcare

Year 2024, Volume: 1 Issue: 1, 13 - 23, 28.04.2024

Emrah Atılgan

Abstract

Artificial intelligence (AI) has a revolutionary impact on the healthcare sector, offering innovative solutions that can lead to significant transformation. Utilizing capabilities such as machine learning, virtual health assistants, natural language processing, robotics, and computer vision, AI technologies enable healthcare professionals to analyze extensive medical data rapidly and accurately. Algorithms driven by AI contribute to early disease diagnosis, risk assessment, and the creation of personalized treatment plans, enhancing the delivery of beneficial solutions to patients and providing more cost-effective healthcare services. In addition to clinical applications, AI shapes healthcare management through patient management, resource allocation, and predictive analytics tools. It is known that AI-supported solutions optimize healthcare services by reducing costs and improving the quality of care. The aim of this article is to elucidate the quantitative and qualitative characteristics of AI in healthcare. Methodologically, a comprehensive bibliometric analysis of academic publications related to AI in healthcare was conducted, presenting information on research and knowledge dissemination at the intersection of this critical technology and the healthcare sector's development. Between 1992 and 2023, 1966 studies indexed in Web of Science, contributed by 7460 authors, were examined. The United States emerged as the leading country in terms of the highest number of studies and citations, with IEEE Access being the leading journal. The most prolific author in this field was Yang Zang, while Diana J. Cook was the most cited author, with the article titled “Ambient intelligence: Technologies, applications, and opportunities,” authored by Diana J. Cook and colleagues, being the most cited article. The most notable topics in this field were “artificial intelligence,” “deep learning,” “machine learning,” and “COVID-19.” The results indicate a significant increase in the use of AI in the healthcare sector in recent years, with this trend expected to continue growing in the coming years. Understanding current trends, major contributors, and evolving aspects of interest provides valuable practical insights for stakeholders aiming to fully leverage the potential of AI in healthcare. Considering that AI is rapidly developing, it can be predicted that its role in health will become more important by contributing to more efficient healthcare systems such as more reliable patient outcomes and increased accessibility. Possible contributions of the obtained results for studies and applications in this field, aspects that need improvement and limitations are discussed in the discussion section.

Keywords

Artificial Intelligence, Healthcare, Deep Learning, Machine Learning

Sağlıkta Yapay Zeka Araştırmalarının Bibliyometrik Analizi

Abstract

Yapay zekâ (YZ), sağlık sektöründe devrim niteliğinde bir etkiye sahip olup, sektörde önemli bir dönüşüme neden olabilecek yenilikçi çözümler sunmaktadır. YZ teknolojilerinden, makine öğrenmesi, sanal sağlık asistanları, doğal dil işleme, robotik ve bilgisayar görüsü gibi imkânların kullanılması, sağlık profesyonellerine geniş kapsamlı tıbbi verileri hızlı ve doğru bir şekilde analiz etme olanağı tanır. YZ tarafından yönlendirilen algoritmalar, hastalıkların erken teşhisine, risk değerlendirmesine ve kişiselleştirilmiş tedavi planlarının oluşturulmasına katkıda bulunarak hastaya sunulacak faydalı çözümleri artırır ve daha ekonomik sağlık hizmetleri sunar. Klinik uygulamaların yanı sıra, YZ, hasta yönetimi, kaynak tahsisi ve öngörüsel analitik araçlarıyla sağlık yönetimini de şekillendirmektedir. YZ tarafından desteklenen çözümlerle sağlık hizmetlerinin optimize edilmesinin maliyetleri düşürdüğü ve bakım kalitesini artırdığı bilinmektedir. Bu makalenin amacı, sağlıkta yapay zekanın nicel ve nitel özelliklerini ortaya koymaktır. Yöntem olarak, sağlıkta YZ ile ilgili akademik yayınlara yönelik kapsamlı bir bibliyometrik analiz yapılmış ve bu kritik teknoloji ile sağlık sektörünün kesişimindeki araştırma ve bilgi yayma alanındaki gelişimle ilgili bilgi sunulmuştur. 1992-2023 yılları arasında, 7460 yazarın katkıda bulunduğu, Web of Science’ta taranan 1966 çalışma incelenmiştir. Bu alanda en çok çalışma üreten ve atıf alan ülke Amerika Birleşik Devletleri, IEEE Access lider dergi olarak bulunmuştur. En çok yayın yapan yazar Yang Zang, en çok atıf alan yazar Diana J. Cook ve en çok atıf alan makale Diana J. Cook ve arkadaşlarının yazdığı “Ambient intelligence: Technologies, applications, and opportunities” başlıklı çalışma olmuştur. Alanda en dikkat çeken konular “yapay zeka,” “derin öğrenme,” “makine öğrenmesi,” ve “COVID-19” olmuştur. Sonuçlar, yapay zekanın sağlık sektöründe kullanımının son yıllarda önemli ölçüde arttığını ve bu trendin önümüzdeki yıllarda da artarak devam etmesinin beklendiğini göstermektedir. Mevcut eğilimlere, başlıca katkıda bulunanlara ve ilgi alanlarının gelişen yönlerine dair bilgi sahibi olmak, sağlıkta YZ'nin potansiyelini tam anlamıyla kullanmayı amaçlayan paydaşlar için değerli pratik bilgiler sunmaktadır. YZ’nin hızla geliştiği dikkate alındığında, sağlıktaki rolünün de daha güvenilir hasta sonuçları, artan erişilebilirlik gibi daha verimli sağlık sistemleri sunulmasına katkı sağlayarak daha önemli hale geleceği öngörülebilir. Elde edilen sonuçların bu alanda yapılacak çalışmalar ve uygulamalar için olası katkıları, geliştirilmesi gereken yanları ve sınırlılıkları tartışma bölümünde ele alınmıştır.

Keywords

Yapay Zeka, Sağlık, Derin Öğrenme, Makine Öğrenmesi

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