Machine Learning for Health (ML4H) 2019: What Makes Machine Learning in Medicine Different?

被引:0
|
作者
Dalca, Adrian V. [1 ,2 ]
Mcdermott, Matthew [3 ]
Alsentzer, Emily [3 ,4 ]
Finlayson, Sam [3 ,4 ]
Oberst, Michael [3 ]
Falck, Fabian [5 ]
Chivers, Corey [6 ]
Beam, Andrew L. [7 ]
Naumann, Tristan [8 ]
Beaulieu-Jones, Brett [4 ]
机构
[1] MIT, EECS, Cambridge, MA 02139 USA
[2] Harvard Med Sch, Radiol, Boston, MA 02115 USA
[3] MIT, CSAIL, Cambridge, MA 02139 USA
[4] Harvard Med Sch, Dept Biomed Informat, Boston, MA 02115 USA
[5] Carnegie Mellon Univ, Sch Comp Sci, Pittsburgh, PA 15213 USA
[6] Univ Penn Hlth Syst, Predict Hlth Care Grp, Philadelphia, PA USA
[7] Harvard TH Chan Sch Publ Hlth, Dept Epidemiol, Boston, MA USA
[8] Microsoft Res, Redmond, WA USA
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 / 9
页数:9
相关论文
共 50 条
  • [31] Machine Learning (ML) Support to Information Fusion
    Waltz, Ed
    SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXVIII, 2019, 11018
  • [32] Snap ML: A Hierarchical Framework for Machine Learning
    Dunner, Celestine
    Parnell, Thomas
    Sarigiannis, Dimitrios
    Ioannou, Nikolas
    Anghel, Andreea
    Ravi, Gummadi
    Kandasamy, Madhusudanan
    Pozidis, Haralampos
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), 2018, 31
  • [33] Dlib-ml: A Machine Learning Toolkit
    King, Davis E.
    JOURNAL OF MACHINE LEARNING RESEARCH, 2009, 10 : 1755 - 1758
  • [34] Greg, ML – Machine Learning for Healthcare at a Scale
    Paola Lapadula
    Giansalvatore Mecca
    Donatello Santoro
    Luisa Solimando
    Enzo Veltri
    Health and Technology, 2020, 10 : 1485 - 1495
  • [35] Machine Learning (ML)-Based Lithography Optimizations
    Shim, Seongbo
    Choi, Suhyeong
    Shin, Youngsoo
    2016 IEEE ASIA PACIFIC CONFERENCE ON CIRCUITS AND SYSTEMS (APCCAS), 2016, : 530 - 533
  • [36] Machine Learning at Microsoft with ML.NET
    Ahmed, Zeeshan
    Amizadeh, Saeed
    Bilenko, Mikhail
    Carr, Rogan
    Chin, Wei-Sheng
    Dekel, Yael
    Dupre, Xavier
    Eksarevskiy, Vadim
    Filipi, Senja
    Finley, Tom
    Goswami, Abhishek
    Hoover, Monte
    Inglis, Scott
    Interlandi, Matteo
    Kazmi, Najeeb
    Krivosheev, Gleb
    Luferenko, Pete
    Matantsev, Ivan
    Matusevych, Sergiy
    Moradi, Shahab
    Nazirov, Gani
    Ormont, Justin
    Oshri, Gal
    Pagnoni, Artidoro
    Parmar, Jignesh
    Roy, Prabhat
    Siddiqui, Mohammad Zeeshan
    Weimer, Markus
    Zahirazami, Shauheen
    Zhu, Yiwen
    KDD'19: PROCEEDINGS OF THE 25TH ACM SIGKDD INTERNATIONAL CONFERENCCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2019, : 2448 - 2458
  • [37] Greg, ML - Machine Learning for Healthcare at a Scale
    Lapadula, Paola
    Mecca, Giansalvatore
    Santoro, Donatello
    Solimando, Luisa
    Veltri, Enzo
    HEALTH AND TECHNOLOGY, 2020, 10 (06) : 1485 - 1495
  • [38] Advancement in machine learning (Ml) and knowledge mining
    Tanwar, Poonam
    Jain, Vishal
    Recent Patents on Engineering, 2019, 13 (01): : 3 - 4
  • [39] Java-ML: A machine learning library
    Abeel, Thomas
    Van De Peer, Yves
    Saeys, Yvan
    Journal of Machine Learning Research, 2009, 10 : 931 - 934
  • [40] AI for AA: machine learning makes an entry
    Kulasekararaj, Austin G.
    BLOOD, 2023, 141 (17) : 2040 - 2042