会议简介:临床医学中的人工智能:人机界面上的生成和交互系统。

Sajjad Fouladvand, Emma Pierson, Ivana Jankovic, David Ouyang, Jonathan H Chen, Roxana Daneshjou
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引用次数: 0

摘要

人工智能(AI)模型大大提高了分析复杂和多维数据集的能力。生成式人工智能和深度学习模型在从非结构化文本、图像以及结构化和表格数据中提取知识方面取得了显著进步。人工智能领域的这一最新突破激发了医学研究的灵感,开发出了许多用于创建临床决策支持系统、监测工具、图像解读和分流功能的工具。然而,要评估人工智能系统在医疗保健领域的潜在影响和意义,全面的研究势在必行。在 2024 年太平洋生物计算研讨会(PSB)题为 "人工智能在临床医学中的应用 "的会议上,与会代表就人工智能在医疗保健领域的应用进行了深入探讨:人机界面上的生成和交互系统 "分会上,我们将重点介绍开发和应用人工智能算法解决医疗保健领域实际问题的研究。
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Session Introduction: Artificial Intelligence in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface.

Artificial Intelligence (AI) models are substantially enhancing the capability to analyze complex and multi-dimensional datasets. Generative AI and deep learning models have demonstrated significant advancements in extracting knowledge from unstructured text, imaging as well as structured and tabular data. This recent breakthrough in AI has inspired research in medicine, leading to the development of numerous tools for creating clinical decision support systems, monitoring tools, image interpretation, and triaging capabilities. Nevertheless, comprehensive research is imperative to evaluate the potential impact and implications of AI systems in healthcare. At the 2024 Pacific Symposium on Biocomputing (PSB) session entitled "Artificial Intelligence in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface", we spotlight research that develops and applies AI algorithms to solve real-world problems in healthcare.

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