TY  - JOUR
T1  - Halk Sağlığı Hemşireliğinde Yapay Zeka Tabanlı GPT-3’ün Kullanılmasına Yönelik Fizibilite Çalışması
TT  - Feasibility Study for Using Artificial Intelligence Based GPT-3 in Public Health Nursing
AU  - Özsezer, Gözde
AU  - Mermer, Gülengül
PY  - 2023
DA  - August
DO  - 10.54061/jphn.1263321
JF  - Halk Sağlığı Hemşireliği Dergisi
JO  - Halk Sag Hem Der
PB  - Halk Sağlığı Hemşireliği Derneği
WT  - DergiPark
SN  - 2667-8047
SP  - 214
EP  - 227
VL  - 5
IS  - 2
LA  - tr
AB  - Bu çalışmanın amacı halk sağlığı hemşireliğinde yapay zeka tabanlı GPT-3’ün kullanılmasına yönelik fizibilite oluşturulmasıdır. Bu fizibilite çalışmasında metin oluşturma ve özetleme için GPT-3'ten birkaç model denendi (text-ada-001, text-babbage-001, text-curie-001, text-davinci-003). Araştırmada OpenAI tarafından Ocak 2023'te ücretsiz beta sürümü sağlanan en yetenekli GPT-3 modeli olarak da bilinen "text-davinci-003"kullanıldı. Bu çalışmada, text-davinci-003, kullanıcıların bir yapay zeka ile basit bir şekilde anında etkileşim kurmasını sağlayan bir doğal dil oluşturma modeli olarak değerlendirildi. Girdi sorgusunda, cevap başına gereken kapasite ve ayrıntılılık yansıtmak için "maksimum uzunluk" parametresi 2048 olarak değiştirildi. GPT-3’ten yanıtlar 9 Mart 2023 tarihinde alındı. GPT-3 için önceden belirlenmiş araştırma soruları sorulmadan önce, yöntem analiz edildi. OpenAI tarafından geliştirilen özel bir model olarak GPT-3'ün ilgili özellikleri kontrol edildi. Özellikle, bu araştırmada kullanılan GPT-3 alıntısı, talep üzerine GPT-3 tarafından önerildi. Bu fizibilite çalışmasında, GPT-3’ün halk sağlığı hemşireliğine katkıları konusunda GPT-3 tarafından oluşturulan 6 amaç doğrultusunda sorulan sorular ve GPT-3 tarafından verilen yanıtlar yer almaktadır. GPT-3'ün, halk sağlığı hemşireliği ile ilgili olası metin blokları bir araya getirilerek, bir ekip üyesi olarak halk sağlığı hemşireliği araştırmalarına katkıda bulunabileceği ifade edilebilir. İnsan yazarlar, yapay zekanın yanı sıra bilimsel literatürü de takip etmesi gerektiği, halk sağlığı hemşireliği alanında yapay zeka katkıları hakkında geniş bir bilimsel tartışmanın gerekli olduğu söylenebilir.
KW  - ChatGPT
KW  - GPT-3
KW  - OpenAI
KW  - yapay zeka
KW  - halk sağlığı hemşireliği
N2  - The aim of this study is to create feasibility for the use of GPT-3, an artificial intelligence-based model, in public health nursing. Several GPT-3 models were tried for text generation and summarization in this feasibility study (text-ada-001, text-babbage-001, text-curie-001, text-davinci-003). The "text-davinci-003" model, which is also known as the most capable GPT-3 model provided in a free beta version by OpenAI in January 2023, was used in this study. In this study, text-davinci-003 was evaluated as a natural language generation model that allows users to interact with an artificial intelligence in a simple way. The "maximum length" parameter was changed to 2048 to reflect the capacity and detail required per response in the input query. Responses from GPT-3 were obtained on March 9, 2023. Prior to asking predetermined research questions for GPT-3, the method was analyzed. The relevant features of GPT-3 as a custom model developed by OpenAI were checked. Specifically, the GPT-3 citation used in this research was suggested by GPT-3 upon request. In this feasibility study, questions were asked and answers were provided by GPT-3 according to 6 purposes generated by GPT-3 regarding the contributions of GPT-3 to public health nursing. It can be stated that GPT-3 can contribute to public health nursing research as a team member by bringing together possible text blocks related to public health nursing. Human writers may need to follow scientific literature in addition to artificial intelligence, and a broad scientific discussion on the contributions of artificial intelligence to public health nursing may be necessary.
CR  - Abd-Alrazaq, A. A., Alajlani, M., Alalwan, A. A., Bewick, B. M., Gardner, P., & Househ, M. (2019). An overview of the features of chatbots in mental health: A scoping review. International Journal of Medical Informatics, 132, 103978. https://doi.org/10.1016/j.ijmedinf.2019.103978
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UR  - https://doi.org/10.54061/jphn.1263321
L1  - https://dergipark.org.tr/en/download/article-file/3003098
ER  -