Exploring the Potential of Artificial Intelligence Language Models in Obstetrics with a Focus on Fetal Medicine: An Evaluation of the Perplexity AI Model.

Abstract

Artificial Intelligence (AI) language models, powered by natural language processing and pretrained language models, have demonstrated proficiency in natural language processing tasks, including text generation and understanding. These models can assist healthcare professionals in Fetal Medicine by providing comprehensive and accurate information, aiding in decision-making processes, and facilitating effective communication between medical practitioners and patients. However, the integration of AI language models in Fetal Medicine faces limitations and challenges. Ethical considerations, privacy concerns, and the potential for algorithmic biases are important factors to be addressed. Transparency and interpretability of AI models are critical to ensure their trustworthiness, and rigorous validation studies are required to evaluate their performance. The involvement of healthcare professionals in the development and implementation of these models is essential to maintain a patient-centered approach and to mitigate the risk of overreliance on AI systems. This article explores the potential benefits and precautions associated with the utilization of AI language models in the context of Fetal Medicine.