Advances, reception and potential of ChatGPT as a tool for healthcare delivery and research: a systematic review.

ChatGPT gained widespread attention for its capabilities in natural language processing, enabling machines to assess human language inputs and generate complex, yet evolving answers. As large language models (LLMs) continue to develop, clear guidelines are needed to help healthcare providers and educators maximise their benefits while mitigating potential risks. This review assessed the utility and accuracy of applying ChatGPT in healthcare assistance, specifically in understanding clinical knowledge and guiding clinical practice and research.

Adopting a consensus on the dose of antenatal steroids used by obstetric and neonatal services in Singapore in anticipation of imminent preterm birth.

In Singapore, glucocorticoids are administered to pregnant women at risk of imminent preterm delivery. The primary desired benefit is maturation of the preterm fetal lung. The commonly used antenatal steroid regimen in Singapore, two doses of 12 mg dexamethasone phosphate at a 12-h interval, is not widely used in other jurisdictions.

ChatGPT outscored human candidates in a virtual objective structured clinical examination in obstetrics and gynecology.

Background: Natural language processing is a form of artificial intelligence that allows human users to interface with a machine without using complex codes. The ability of natural language processing systems, such as ChatGPT, to successfully engage with healthcare systems requiring fluid reasoning, specialist data interpretation, and empathetic communication in an unfamiliar and evolving environment is poorly studied. This study investigated whether the ChatGPT interface could engage with and complete a mock objective structured clinical examination simulating assessment for membership of the Royal College of Obstetricians and Gynaecologists.