AIMC Topic: Turkey

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Investigation of serum neuroserpin levels in pregnant women diagnosed with pre-eclampsia: a prospective case-control study.

BMC pregnancy and childbirth
OBJECTIVE: Neuroserpin, a serine protease inhibitor, is recognized for its anti-inflammatory and neuroprotective properties. Given the central role of inflammation and neurological involvement in the pathophysiology of preeclampsia, this study aimed ...

Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination.

BMC medical education
BACKGROUND: Objective Structured Clinical Examinations (OSCEs) are widely used in medical education to assess students' clinical and professional skills. Recent advancements in artificial intelligence (AI) offer opportunities to complement human eval...

The Relationship Between Anxiety and Readiness Levels Regarding Artificial Intelligence in Midwives: An Intergenerational Comparative Study.

Computers, informatics, nursing : CIN
This study aimed to compare Generations X, Y, and Z in terms of anxiety and readiness levels regarding artificial intelligence and investigate the relationship between anxiety and readiness levels regarding artificial intelligence in midwives across ...

The role of artificial intelligence in medical education: an evaluation of Large Language Models (LLMs) on the Turkish Medical Specialty Training Entrance Exam.

BMC medical education
OBJECTIVE: To evaluate the performance of advanced large language models (LLMs)-OpenAI-ChatGPT 4, Google AI-Gemini 1.5 Pro, Cohere-Command R + and Meta AI-Llama 3 70B on questions from the Turkish Medical Specialty Training Entrance Exam (2021, 1st s...

Assessing the performance of ChatGPT-4o on the Turkish Orthopedics and Traumatology Board Examination.

Joint diseases and related surgery
OBJECTIVES: This study aims to assess the overall performance of ChatGPT version 4-omni (GPT-4o) on the Turkish Orthopedics and Traumatology Board Examination (TOTBE) using actual examinees as a reference point to evaluate and compare the performance...

A validity and reliability study of the artificial intelligence attitude scale (AIAS-4) and its relationship with social media addiction and eating behaviors in Turkish adults.

BMC public health
BACKGROUND: In recent years, there has been a rapid increase in the use of the internet and social media. Billions of people worldwide use social media and spend an average of 2.2 h a day on these platforms. At the same time, artificial intelligence ...

Leveraging large language models to mimic domain expert labeling in unstructured text-based electronic healthcare records in non-english languages.

BMC medical informatics and decision making
BACKGROUND: The integration of big data and artificial intelligence (AI) in healthcare, particularly through the analysis of electronic health records (EHR), presents significant opportunities for improving diagnostic accuracy and patient outcomes. H...

Psychometric properties and Turkish adaptation of the artificial intelligence attitude scale (AIAS-4): evidence for construct validity.

BMC psychology
Artificial intelligence (AI) attitude scales can be used to better evaluate the benefit and drawback cons of AI. This article consists of two different studies examining attitudes towards AI. In Study I (N = 370), the four-item Artificial Intelligenc...

Exploring the role of artificial intelligence in Turkish orthopedic progression exams.

Acta orthopaedica et traumatologica turcica
OBJECTIVE: The aim of this study was to evaluate and compare the performance of the artificial intelligence (AI) models ChatGPT-3.5, ChatGPT-4, and Gemini on the Turkish Specialization Training and Development Examination (UEGS) to determine their ut...

Predicting total healthcare demand using machine learning: separate and combined analysis of predisposing, enabling, and need factors.

BMC health services research
OBJECTIVE: Predicting healthcare demand is essential for effective resource allocation and planning. This study applies Andersen's Behavioral Model of Health Services Use, focusing on predisposing, enabling, and need factors, using data from the 2022...