Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts

Sifting through vast textual data and summarizing key information imposes a substantial burden on how clinicians allocate their time. Although large language models (LLMs) have shown immense promise in natural language processing (NLP) tasks, their efficacy across diverse clinical summarization tasks has not yet been rigorously examined. In this work, we employ domain adaptation methods on eight LLMs, spanning six datasets and four distinct summarization tasks: radiology reports, patient questions, progress notes, and doctor-patient dialogue. Our thorough quantitative assessment reveals trade-offs between models and adaptation methods in addition to instances where recent advances in LLMs may not lead to improved results. Further, in a clinical reader study with six physicians, we depict that summaries from the best adapted LLM are preferable to human summaries in terms of completeness and correctness. Our ensuing qualitative analysis delineates mutual challenges faced by both LLMs and human experts. Lastly, we correlate traditional quantitative NLP metrics with reader study scores to enhance our understanding of how these metrics align with physician preferences. Our research marks the first evidence of LLMs outperforming human experts in clinical text summarization across multiple tasks. This implies that integrating LLMs into clinical workflows could alleviate documentation burden, empowering clinicians to focus more on personalized patient care and other irreplaceable human aspects of medicine.Comment: 23 pages, 22 figure

Scalable Indium Phosphide Thin-Film Nanophotonics Platform for Photovoltaic and Photoelectrochemical Devices

Recent developments in nanophotonics have provided a clear roadmap for improving the efficiency of photonic devices through control over absorption and emission of devices. These advances could prove transformative for a wide variety of devices, such as photovoltaics, photoelectrochemical devices, photodetectors, and light-emitting diodes. However, it is often challenging to physically create the nanophotonic designs required to engineer the optical properties of devices. Here, we present a platform based on crystalline indium phosphide that enables thin-film nanophotonic structures with physical morphologies that are impossible to achieve through conventional state-of-the-art material growth techniques. Here, nanostructured InP thin films have been demonstrated on non-epitaxial alumina inverted nanocone (i-cone) substrates <i>via</i> a low-cost and scalable thin-film vapor–liquid–solid growth technique. In this process, indium films are first evaporated onto the i-cone structures in the desired morphology, followed by a high-temperature step that causes a phase transformation of the indium into indium phosphide, preserving the original morphology of the deposited indium. Through this approach, a wide variety of nanostructured film morphologies are accessible using only control over evaporation process variables. Critically, the as-grown nanotextured InP thin films demonstrate excellent optoelectronic properties, suggesting this platform is promising for future high-performance nanophotonic devices

Confined Liquid-Phase Growth of Crystalline Compound Semiconductors on Any Substrate

The growth of crystalline compound semiconductors on amorphous and non-epitaxial substrates is a fundamental challenge for state-of-the-art thin-film epitaxial growth techniques. Direct growth of materials on technologically relevant amorphous surfaces, such as nitrides or oxides results in nanocrystalline thin films or nanowire-type structures, preventing growth and integration of high-performance devices and circuits on these surfaces. Here, we show crystalline compound semiconductors grown directly on technologically relevant amorphous and non-epitaxial substrates in geometries compatible with standard microfabrication technology. Furthermore, by removing the traditional epitaxial constraint, we demonstrate an <i>atomically sharp lateral heterojunction</i> between indium phosphide and tin phosphide, two materials with vastly different crystal structures, a structure that cannot be grown with standard vapor-phase growth approaches. Critically, this approach enables the growth and manufacturing of crystalline materials without requiring a nearly lattice-matched substrate, potentially impacting a wide range of fields, including electronics, photonics, and energy devices