Concepedia

Machine Learning Risk Models

Machine Learning Risk Models is a computational framework that employs machine learning algorithms to identify, quantify, and predict risk levels by analyzing patterns in multidimensional data, distinguished from traditional risk models by its adaptive learning capability and non-linear modeling of complex, heterogeneous variables within domains such as Customer Risk Rating and Radiation Pneumonitis.

797

Publications

42.3K

Citations

4.8K

Authors

1.7K

Institutions

Publications per year

2017–2026

736

Parents

Publications

797

The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users

Sijia Li, Yilin Wang, Jia Xue et al. · International Journal of Environmental Research and Public Health · 2020 · 1.9K citations · Full text

, , +15

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

Stephen Weng, Jenna Reps, Joe Kai et al. · PLoS ONE · 2017 · 1.3K citations · Full text

, , +17

Hidden technical debt in Machine learning systems

D. Sculley, Gary D. Holt, Daniel Golovin et al. · Neural Information Processing Systems · 2015 · 843 citations

, , +8

Cardiovascular disease risk prediction using automated machine learning: A prospective study of 423,604 UK Biobank participants

Ahmed M. Alaa, Thomas Bolton, Emanuele Di Angelantonio et al. · PLoS ONE · 2019 · 606 citations · Full text

, , +17

A Framework of Potential Sources of Harm Throughout the Machine Learning Life Cycle

Harini Suresh, John V. Guttag · DSpace@MIT (Massachusetts Institute of Technology) · 2021 · 452 citations · Full text

, , +12

1–5 of 797

Authors

4.8K

  1. JV
    John V. Guttag

    Massachusetts Institute of Technology, United States

    5 publications · 597 citations

    5

    h-index

  2. GY
    Gregory Y.H. Lip

    Aalborg University, Denmark

    4 publications · 215 citations

    4

    h-index

  3. LZ
    Lei Zhang

    Monash University, Australia

    3 publications · 164 citations

    3

    h-index

  4. MG
    Matthew Gudgeon

    United States Military Academy, United States

    3 publications · 87 citations

    3

    h-index

  5. RM
    Richard M. Peck

    University of Illinois Chicago, United States

    3 publications · 87 citations

    3

    h-index

1–5 of 4.8K

Institutions

1.7K

  1. Harvard University

    Cambridge, United States

    18 h-index

    74 publications

    6.1K citations

  2. Cornell University

    Ithaca, United States

    11 h-index

    34 publications

    2K citations

  3. Brigham and Women's Hospital

    Boston, United States

    11 h-index

    16 publications

    1.6K citations

  4. Massachusetts Institute of Technology

    Cambridge, United States

    11 h-index

    22 publications

    1.8K citations

  5. Chinese Academy of Sciences

    Beijing, China

    10 h-index

    36 publications

    1.7K citations

  6. Massachusetts General Hospital

    Boston, United States

    9 h-index

    32 publications

    1K citations

  7. Yale University

    New Haven, United States

    9 h-index

    30 publications

    2.2K citations

  8. University of Chinese Academy of Sciences

    Beijing, China

    9 h-index

    18 publications

    2.6K citations

1–8 of 1.7K

Venues

  1. Scientific Reports

    25 publications · 1.1K citations

    20

    h-index

  2. PLoS ONE

    22 publications · 3.1K citations

    18

    h-index

  3. SSRN Electronic Journal

    Repository · 10 publications · 227 citations

    10

    h-index

  4. Sensors

    9 publications · 338 citations

    9

    h-index

  5. BMC Medical Informatics and Decision Making

    8 publications · 287 citations

    8

    h-index

1–5