数据科学
健康信息学
计算机科学
人工智能
信息学
领域(数学)
重大挑战
大数据
深度学习
领域(数学分析)
医疗保健
机器人学
机器学习
数据挖掘
机器人
工程类
政治学
数学分析
电气工程
数学
纯数学
法学
操作系统
作者
Jianing Qiu,Lin Li,Jiankai Sun,Jiachuan Peng,Peilun Shi,Ruiyang Zhang,Yinzhao Dong,Kyle Lam,Frank P.-W. Lo,Bo Xiao,Wu Yuan,Ningli Wang,Dong Xu,Benny Lo
标识
DOI:10.1109/jbhi.2023.3316750
摘要
Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions.Once pretrained, large AI models demonstrate impressive performance in various downstream tasks.A prime example is ChatGPT, whose capability has compelled people's imagination about the farreaching influence that large AI models can have and their potential to transform different domains of our lives.In health informatics, the advent of large AI models has brought new paradigms for the design of methodologies.The scale of multi-modal data in the biomedical and health domain has been ever-expanding especially since the community embraced the era of deep learning, which provides the ground to develop, validate, and advance large AI models for breakthroughs in health-related areas.This article presents a comprehensive review of large AI models, from background to their applications.We identify seven key sectors in which large AI models are applicable and might have substantial influence, including 1) bioinformatics; 2) medical diagnosis; 3) medical imaging; 4) medical
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