Informatics and machine learning methods for health applications

被引:0
|
作者
Li Shen
Xinghua Shi
Zhongming Zhao
Kai Wang
机构
[1] University of Pennsylvania,Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine
[2] Temple University,Department of Computer and Information Sciences, College of Science and Technology
[3] The University of Texas Health Science Center at Houston,Center for Precision Health, School of Biomedical Informatics
[4] Childrens Hospital of Philadelphia,Raymond G. Perelman Center for Cellular and Molecular Therapeutics
关键词
D O I
暂无
中图分类号
学科分类号
摘要
The 2020 International Conference on Intelligent Biology and Medicine (ICIBM 2020) provided a multidisciplinary forum for computational scientists and experimental biologists to share recent advances on all aspects of intelligent computing, informatics and data science in biology and medicine. ICIBM 2020 was held as a virtual conference on August 9–10, 2020, including four live sessions with forty-one oral presentations over video conferencing. In this special issue, ten high-quality manuscripts were selected after peer-review from seventy-five submissions to represent the medical informatics and decision making aspect of the conference. In this editorial, we briefly summarize these ten selected manuscripts.
引用
收藏
相关论文
共 50 条
  • [21] Mechanistic Machine Learning:Theory, Methods, and Applications
    Paris Perdikaris
    Shaoqiang Tang
    Theoretical & Applied Mechanics Letters, 2020, (03) : 141 - 142
  • [22] Machine learning for synthetic biology: Methods and applications
    Hu, Ruyun
    Zhang, Songya
    Meng, Hailin
    Yu, Han
    Zhang, Jianzhi
    Luo, Xiaozhou
    Si, Tong
    Liu, Chenli
    Qiao, Yu
    CHINESE SCIENCE BULLETIN-CHINESE, 2021, 66 (03): : 284 - 299
  • [23] Machine learning methods and systems for data-driven discovery in biomedical informatics
    Yoon, Sungroh
    Lee, Seunghak
    Wang, Wei
    METHODS, 2017, 129 : 1 - 2
  • [24] Machine learning and deep learning methods for wireless network applications
    Abel C. H. Chen
    Wen-Kang Jia
    Feng-Jang Hwang
    Genggeng Liu
    Fangying Song
    Lianrong Pu
    EURASIP Journal on Wireless Communications and Networking, 2022
  • [25] Machine learning and deep learning methods for wireless network applications
    Chen, Abel C. H.
    Jia, Wen-Kang
    Hwang, Feng-Jang
    Liu, Genggeng
    Song, Fangying
    Pu, Lianrong
    EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2022, 2022 (01)
  • [26] Informatics and machine learning to define the phenotype
    Basile, Anna Okula
    Ritchie, Marylyn DeRiggi
    EXPERT REVIEW OF MOLECULAR DIAGNOSTICS, 2018, 18 (03) : 219 - 226
  • [27] Machine Learning and Imaging Informatics in Oncology
    Tseng, Huan-Hsin
    Wei, Lise
    Cu, Sunan
    Luo, Yi
    Ten Haken, Randall K.
    El Naqa, Issam
    ONCOLOGY, 2020, 98 (06) : 344 - 362
  • [28] Biomedical informatics with optimization and machine learning
    Huang, Shuai
    Zhou, Jiayu
    Wang, Zhangyang
    Ling, Qing
    Shen, Yang
    Eurasip Journal on Bioinformatics and Systems Biology, 2016, 2017 (01)
  • [29] A Machine Learning Tool for Materials Informatics
    Wang, Zhi-Lei
    Ogawa, Toshio
    Adachi, Yoshitaka
    ADVANCED THEORY AND SIMULATIONS, 2020, 3 (01)
  • [30] Machine Learning in Ecosystem Informatics and Sustainability
    Dietterich, Thomas G.
    21ST INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (IJCAI-09), PROCEEDINGS, 2009, : 8 - 13