中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 中国科学院分子影像重点实验室
From Signal to Knowledge: The Diagnostic Value of Raw Data in the Artificial Intelligence Prediction of Human Data for the First Time

文献类型：期刊论文

作者He, Bingxi1,2,3; Guo, Yu4; Zhu, Yongbei1,2,3; Tong, Lixia5; Kong, Boyu; Wang, Kun3; Sun, Caixia1,2,3; Li, Hailin1,2,3; Huang, Feng5; Wu, Liwei6
刊名ENGINEERING
出版日期2024-03-01
卷号34页码:60-69
关键词Computed tomography Diagnosis Deep learning Lung cancer Raw data
ISSN号2095-8099
DOI10.1016/j.eng.2023.02.013
通讯作者Dong, Di(di.dong@ia.ac.cn) ; Zhang, Huimao(huimao@jlu.edu.cn) ; Tian, Jie(jie.tian@ia.ac.cn)
英文摘要Encouraging and astonishing developments have recently been achieved in image-based diagnostic technology. Modern medical care and imaging technology are becoming increasingly inseparable. However, the current diagnosis pattern of signal to image to knowledge inevitably leads to information distortion and noise introduction in the procedure of image reconstruction (from signal to image). Artificial intelligence (AI) technologies that can mine knowledge from vast amounts of data offer opportunities to disrupt established workflows. In this prospective study, for the first time, we develop an AI-based signal-toknowledge diagnostic scheme for lung nodule classification directly from the computed tomography (CT) raw data (the signal). We find that the raw data achieves almost comparable performance with CT, indicating that it is possible to diagnose diseases without reconstructing images. Moreover, the incorporation of raw data through three common convolutional network structures greatly improves the performance of the CT models in all cohorts (with a gain ranging from 0.01 to 0.12), demonstrating that raw data contains diagnostic information that CT does not possess. Our results break new ground and demonstrate the potential for direct signal-to-knowledge domain analysis. (c) 2023 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering and Higher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
WOS关键词IMAGE-RECONSTRUCTION ; LUNG-CANCER ; DEEP ; RADIOMICS
资助项目National Key Research and Development Program of China[2017YFA0205200] ; National Key Research and Development Program of China[2023YFC2415200] ; National Key Research and Development Program of China[2021YFF1201003] ; National Key Research and Development Program of China[2021YFC2500402] ; National Natural Science Foundation of China[82022036] ; National Natural Science Foundation of China[91959130] ; National Natural Science Foundation of China[81971776] ; National Natural Science Foundation of China[62027901] ; National Natural Science Foundation of China[81930053] ; National Natural Science Foundation of China[81771924] ; National Natural Science Foundation of China[62333022] ; National Natural Science Foundation of China[82361168664] ; National Natural Science Foundation of China[62176013] ; National Natural Science Foundation of China[82302317] ; Beijing Natural Science Foundation[Z20J00105] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB38040200] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Project of High-Level Talents Team Introduction in Zhuhai City (Zhuhai)[HLHPTP201703] ; Youth Innovation Promotion Association CAS[Y2021049] ; China Postdoctoral Science Foundation[2021M700341]
WOS研究方向Engineering
语种英语
WOS记录号WOS:001249283700001
出版者ELSEVIER
资助机构National Key Research and Development Program of China ; National Natural Science Foundation of China ; Beijing Natural Science Foundation ; Strategic Priority Research Program of Chinese Academy of Sciences ; Chinese Academy of Sciences ; Project of High-Level Talents Team Introduction in Zhuhai City (Zhuhai) ; Youth Innovation Promotion Association CAS ; China Postdoctoral Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/59097]  
专题自动化研究所_中国科学院分子影像重点实验室
通讯作者Dong, Di; Zhang, Huimao; Tian, Jie
作者单位1.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Engn Med, Beijing 100191, Peoples R China
2.Beihang Univ, Key Lab Big Data Based Precis Med, Minist Ind & Informat Technol, Beijing 100191, Peoples R China
3.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
4.First Hosp Jilin Univ, Dept Radiol, Changchun 130021, Peoples R China
5.Neusoft Med Syst Co Ltd, Shenyang 110167, Peoples R China
6.Neusoft Res Intelligent Healthcare Technol Co Ltd, Shenyang 110167, Peoples R China
7.Xidian Univ, Sch Life Sci & Technol, Xian 710126, Peoples R China
8.Minist Educ, Engn Res Ctr Mol & Neuro Imaging, Xian 710126, Peoples R China
9.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 He, Bingxi,Guo, Yu,Zhu, Yongbei,et al. From Signal to Knowledge: The Diagnostic Value of Raw Data in the Artificial Intelligence Prediction of Human Data for the First Time[J]. ENGINEERING,2024,34:60-69.
APA He, Bingxi.,Guo, Yu.,Zhu, Yongbei.,Tong, Lixia.,Kong, Boyu.,...&Tian, Jie.(2024).From Signal to Knowledge: The Diagnostic Value of Raw Data in the Artificial Intelligence Prediction of Human Data for the First Time.ENGINEERING,34,60-69.
MLA He, Bingxi,et al."From Signal to Knowledge: The Diagnostic Value of Raw Data in the Artificial Intelligence Prediction of Human Data for the First Time".ENGINEERING 34(2024):60-69.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。