Exploring Early Perceptions and Experiences of ChatGPT in Pediatric Critical Care: A Qualitative Study Among Health Care Professionals.

To optimize the deployment of Generative Artificial Intelligence in health care, it's essential for health care professionals (HCPs) to understand these technologies' capabilities and constraints. This study explores HCPs' initial impressions and experiences using ChatGPT, a Generative Pre-trained Transformer, in Pediatric Critical Care Units (PICUs). By conducting focus groups with a diverse set of HCPs, we aimed to assess their awareness, utilization, perceived benefits, and concerns about incorporating ChatGPT into their PICUs.

Presentations and outcomes of familial hemophagocytic lymphohistiocytosis in the pediatric intensive care units (PICUs).

Objectives: We aimed to describe Familial Hemophagocytic Lymphohistiocytosis (F-HLH) patients' clinical features, intensive care courses, and outcomes.

Methods: Multi-center retrospective cohort study of pediatric patients diagnosed with F-HLH from 2015 to 2020 in five tertiary centers in Saudi Arabia. Patients were classified as F-HLH based on their genetic confirmation of known mutation or on their clinical criteria, which include a constellation of abnormalities, early disease onset, recurrent HLH in the absence of other causes, or a family history of HLH.

Enhancing Expert Panel Discussions in Pediatric Palliative Care: Innovative Scenario Development and Summarization With ChatGPT-4.

This study presents a novel approach to enhance expert panel discussions in a medical conference through the use of ChatGPT-4 (Generative Pre-trained Transformer version 4), a recently launched powerful artificial intelligence (AI) language model. We report on ChatGPT-4's ability to optimize and summarize the medical conference panel recommendations of the first Pan-Arab Pediatric Palliative Critical Care Hybrid Conference, held in Riyadh, Saudi Arabia. ChatGPT-4 was incorporated into the discussions in two sequential phases: first, scenarios were optimized by the AI model to stimulate in-depth conversations; second, the model identified, summarized, and contrasted key themes from the panel and audience discussions.