Early prediction of long COVID-19 syndrome persistence at 12 months after hospitalisation: a prospective observational study from Ukraine.

Objective: To identify the early predictors of a self-reported persistence of long COVID syndrome (LCS) at 12 months after hospitalisation and to propose the prognostic model of its development.

Design: A combined cross-sectional and prospective observational study.

Setting: A tertiary care hospital.

Exploring ChatGPT in clinical inquiry: a scoping review of characteristics, applications, challenges, and evaluation.

Introduction: Recent advancements in generative AI, exemplified by ChatGPT, hold promise for healthcare applications such as decision-making support, education, and patient engagement. However, rigorous evaluation is crucial to ensure reliability and safety in clinical contexts. This scoping review explores ChatGPT's role in clinical inquiry, focusing on its characteristics, applications, challenges, and evaluation.

The state of artificial intelligence in medical research: A survey of corresponding authors from top medical journals.

Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond to human language through Large Language Models (LLMs)‥ These models have diverse applications in fields such as medical research, scientific writing, and publishing, but concerns such as hallucination, ethical issues, bias, and cybersecurity need to be addressed. To understand the scientific community's understanding and perspective on the role of Artificial Intelligence (AI) in research and authorship, a survey was designed for corresponding authors in top medical journals. An online survey was conducted from July 13th, 2023, to September 1st, 2023, using the SurveyMonkey web instrument, and the population of interest were corresponding authors who published in 2022 in the 15 highest-impact medical journals, as ranked by the Journal Citation Report.

A Road Map of Prompt Engineering for ChatGPT in Healthcare: A Perspective Study.

Generative AI models, such as ChatGPT, have significantly impacted healthcare through the strategic use of prompts to enhance precision, relevance, and ethical standards. This perspective explores the application of prompt engineering to tailor outputs specifically for healthcare stakeholders: patients, providers, policymakers, and researchers. A nine-stage process for prompt engineering in healthcare is proposed, encompassing identifying applications, understanding stakeholder needs, designing tailored prompts, iterative testing and refinement, ethical considerations, collaborative feedback, documentation, training, and continuous updates.