AI: A transformative opportunity in cell biology.

The success of artificial intelligence (AI) algorithms in predicting protein structure and more recently, protein interactions, demonstrates the power and potential of machine learning and AI for advancing and accelerating biomedical research. As cells are the fundamental unit of life, applying these tools to understand and predict cellular function represents the next great challenge. However, given the complexity of cellular structure and function, the diversity of cell types and the dynamic plasticity of cell states, the task will not be easy.

CZ CELLxGENE Discover: a single-cell data platform for scalable exploration, analysis and modeling of aggregated data.

Hundreds of millions of single cells have been analyzed using high-throughput transcriptomic methods. The cumulative knowledge within these datasets provides an exciting opportunity for unlocking insights into health and disease at the level of single cells. Meta-analyses that span diverse datasets building on recent advances in large language models and other machine-learning approaches pose exciting new directions to model and extract insight from single-cell data.

Large Language Model Influence on Diagnostic Reasoning: A Randomized Clinical Trial.

Importance: Large language models (LLMs) have shown promise in their performance on both multiple-choice and open-ended medical reasoning examinations, but it remains unknown whether the use of such tools improves physician diagnostic reasoning.

Objective: To assess the effect of an LLM on physicians' diagnostic reasoning compared with conventional resources.

Design, Setting, And Participants: A single-blind randomized clinical trial was conducted from November 29 to December 29, 2023.