以下内容为 AI 自动翻译，英文原文附后供参考。
摘要
最近医学人工智能的进展促成了以人为本的医学图像分析（PecMan）框架的推出，旨在增强人工智能技术在临床环境中的整合。PecMan强调公平性、诊断准确性和工作流程效率的重要性，解决了历史上阻碍人工智能在医疗保健中采用的重大挑战。通过关注性能偏差和工作流程中断，该框架旨在为医疗提供者和患者创造一个更公平和高效的环境。
Recent advancements in medical AI have led to the introduction of the People-Centred Medical Image Analysis (PecMan) framework, which aims to enhance the integration of AI technologies in clinical settings. PecMan emphasizes the importance of fairness, diagnostic accuracy, and workflow efficiency, addressing significant challenges that have historically hindered the adoption of AI in healthcare. By focusing on performance biases and workflow disruptions, this framework seeks to create a more equitable and efficient environment for both healthcare providers and patients.
要点
PecMan框架关注医学人工智能中的公平性和准确性。
PecMan framework focuses on fairness and accuracy in medical AI.
该框架旨在减少临床人工智能应用中的性能偏差。
The framework aims to reduce performance biases in clinical AI applications.
提高工作流程效率是PecMan倡议的关键目标。
Improving workflow efficiency is a key goal of the PecMan initiative.
为何重要
PecMan框架的发展代表了使人工智能技术在医疗保健中更易获得和有效的重要一步，最终改善患者结果和对医疗系统的信任。
The development of the PecMan framework represents a significant step towards making AI technologies more accessible and effective in healthcare, ultimately improving patient outcomes and trust in medical systems.
产品经理
对于产品经理而言，理解PecMan框架至关重要，因为它强调了优先考虑用户体验和公平性的人工智能解决方案的必要性，这可以为产品开发和市场策略提供指导。
For product managers, understanding the PecMan framework is crucial as it highlights the need for AI solutions that prioritize user experience and equity, which can inform product development and market strategies.
开发者
开发者和工程师应关注PecMan，因为它概述了构建不仅在技术上可靠而且在社会责任和临床工作流程上对齐的人工智能系统的关键考虑因素。
Developers and engineers should pay attention to PecMan as it outlines critical considerations for building AI systems that are not only technically sound but also socially responsible and aligned with clinical workflows.
学生与求职者
对于学生和求职者而言，像PecMan这样的框架的出现表明对能够弥合人工智能技术与医疗保健之间差距的专业人才的需求日益增长，突显了在快速发展的领域中的机会。
For students and job-seekers, the emergence of frameworks like PecMan indicates a growing demand for professionals who can bridge the gap between AI technology and healthcare, highlighting opportunities in a rapidly evolving field.
覆盖来源
来源标题与摘录保留原文，以便核对与追溯。
arXiv cs.LG
People-Centred Medical Image AnalysisResearchers introduced People-Centred Medical Image Analysis (PecMan), a framework aimed at enhancing AI integration in clinical settings by focusing on fairness, diagnostic accuracy, and workflow efficiency. The framework addresses key challenges such as performance biases and workflow disruptions that impede AI adoption in healthcare.