AI as an intervention: improving clinical outcomes relies on a causal approach to AI development and validation.

The primary practice of healthcare artificial intelligence (AI) starts with model development, often using state-of-the-art AI, retrospectively evaluated using metrics lifted from the AI literature like AUROC and DICE score. However, good performance on these metrics may not translate to improved clinical outcomes. Instead, we argue for a better development pipeline constructed by working backward from the end goal of positively impacting clinically relevant outcomes using AI, leading to considerations of causality in model development and validation, and subsequently a better development pipeline.

Myocardial Fibroblast Activation After Acute Myocardial Infarction: A Positron Emission Tomography and Magnetic Resonance Study.

Background: Myocardial fibrosis is a key healing response after myocardial infarction driven by activated fibroblasts. Gallium-68-labeled fibroblast activation protein inhibitor ([Ga]-FAPI) is a novel positron-emitting radiotracer that binds activated fibroblasts.

Objectives: The aim of this study was to investigate the intensity, distribution, and time-course of fibroblast activation after acute myocardial infarction.

Advances in Natural-Product-Based Fluorescent Agents and Synthetic Analogues for Analytical and Biomedical Applications.

Fluorescence is a remarkable property exhibited by many chemical compounds and biomolecules. Fluorescence has revolutionized analytical and biomedical sciences due to its wide-ranging applications in analytical and diagnostic tools of biological and environmental importance. Fluorescent molecules are frequently employed in drug delivery, optical sensing, cellular imaging, and biomarker discovery.