Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All

被引：0
|
作者：
Sarkar, Suproteem K. [1 ]
Roy, Subhrajit [2 ]
Alsentzer, Emily [3 ,4 ]
McDermott, Matthew B. A. [3 ]
Falck, Fabian [5 ]
Bica, Ioana [5 ]
Adams, Griffin [6 ]
Pfohl, Stephen [7 ]
Beaulieu-Jones, Brett [4 ]
Naumann, Tristan [8 ]
Hyland, Stephanie L. [8 ]
机构：
[1] Harvard Univ, Cambridge, MA 02138 USA
[2] Google Brain, Mountain View, CA USA
[3] MIT, Cambridge, MA 02139 USA
[4] Harvard Med Sch, Boston, MA 02115 USA
[5] Univ Oxford, Oxford, England
[6] Columbia Univ, New York, NY 10027 USA
[7] Stanford Univ, Stanford, CA 94305 USA
[8] Microsoft Res, Redmond, WA USA
来源：
MACHINE LEARNING FOR HEALTH, VOL 136 | 2020年 / 136卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
引用
收藏
页码：1 / 11
页数：11
相关论文
共 50 条
  • [41] DB4ML-An In-Memory Database Kernel with Machine Learning Support
    Jasny, Matthias
    Ziegler, Tobias
    Kraska, Tim
    Roehm, Uwe
    Binnig, Carsten
    SIGMOD'20: PROCEEDINGS OF THE 2020 ACM SIGMOD INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2020, : 159 - 173
  • [42] The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights
    Gasse, Maxime
    Bowly, Simon
    Cappart, Quentin
    Charfreitag, Jonas
    Charlin, Laurent
    Chetelat, Didier
    Chmiela, Antonia
    Dumouchelle, Justin
    Gleixner, Ambros
    Kazachkov, Aleksandr M.
    Khalil, Elias
    Lichocki, Pawel
    Lodi, Andrea
    Lubin, Miles
    Maddison, Chris J.
    Morris, Christopher
    Papageorgiou, Dimitri J.
    Parjadis, Augustin
    Pokutta, Sebastian
    Prouvost, Antoine
    Scavuzzo, Lara
    Zarpellon, Giulia
    Yang, Linxin
    Lai, Sha
    Wang, Akang
    Luo, Xiaodong
    Zhou, Xiang
    Huang, Haohan
    Shao, Shengcheng
    Zhu, Yuanming
    Zhang, Dong
    Quan, Tao
    Cao, Zixuan
    Xu, Yang
    Huang, Zhewei
    Zhou, Shuchang
    Chen Binbin
    He Minggui
    Hao Hao
    Zhang Zhiyu
    An Zhiwu
    Mao Kun
    NEURIPS 2021 COMPETITIONS AND DEMONSTRATIONS TRACK, VOL 176, 2021, 176 : 220 - 231
  • [43] A Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization
    Wang, Qianwen
    Chen, Zhutian
    Wang, Yong
    Qu, Huamin
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2022, 28 (12) : 5134 - 5153
  • [44] RETRACTED ARTICLE: Application of machine learning (ML) and internet of things (IoT) in healthcare to predict and tackle pandemic situation
    R. Sitharthan
    M. Rajesh
    Distributed and Parallel Databases, 2022, 40 : 887 - 887
  • [45] Advancing grading and outcome prediction in aneurysmal subarachnoid hemorrhage: Harnessing artificial intelligence and machine learning for precision healthcare
    Farooqi, Hanzala Ahmed
    Safwan, Zenia
    Nabi, Rayyan
    NEUROSURGICAL REVIEW, 2024, 47 (01)
  • [46] THE INFLUENCE OF SOCIAL DETERMINANTS OF HEALTH ON HEALTHCARE ACCESS, UTILIZATION, AND TREATMENTS IN ATOPIC DERMATITIS PATIENTS USING ALL OF US AND MACHINE LEARNING METHODS
    Shaw, D.
    Irwin, K.
    Stolshek, B.
    Saber, J.
    Kennedy, L.
    VALUE IN HEALTH, 2024, 27 (06) : S276 - S276
  • [47] Advancing healthcare with artificial intelligence: diagnostic accuracy of machine learning algorithm in diagnosis of diabetic retinopathy in the Brazilian population
    dos Reis, Mateus A.
    Kunas, Cristiano A.
    Araujo, Thiago da Silva
    Schneiders, Josiane
    de Azevedo, Pietro B.
    Nakayama, Luis F.
    Rados, Dimitris R. V.
    Umpierre, Roberto N.
    Berwanger, Otavio
    Lavinsky, Daniel
    Malerbi, Fernando K.
    Navaux, Philippe O. A.
    Schaan, Beatriz D.
    DIABETOLOGY & METABOLIC SYNDROME, 2024, 16 (01):
  • [48] Reliability and Validity of an Automated Model for Assessing the Learning of Machine Learning in Middle and High School: Experiences from the "ML for All!" Course
    Rauber, Marcelo Fernando
    Von Wangenheim, Christiane Gresse
    Barbetta, Pedro Alberto
    Borgatto, Adriano Ferreti
    Martins, Ramon Mayor
    Hauck, Jean Carlo Rossa
    INFORMATICS IN EDUCATION, 2024, 23 (02): : 409 - 437
  • [49] The Art of the Algorithm: Machine Learning in Environmental Health Research, with Nicole Kleinstreuer (vol 2020, 467, 2020)
    Ahearn, Ashley
    ENVIRONMENTAL HEALTH PERSPECTIVES, 2020, 128 (03)
  • [50] Machine Learning Healthcare Applications (ML-HCAs) Are No Stand-Alone Systems but Part of an Ecosystem - A Broader Ethical and Health Technology Assessment Approach is Needed
    Gerhards, Helene
    Weber, Karsten
    Bittner, Uta
    Fangerau, Heiner
    AMERICAN JOURNAL OF BIOETHICS, 2020, 20 (11): : 46 - 48
12345