Predictive Analytics For Prevention

Predictive Analytics for Prevention is a computational methodology within preventive care informatics that employs statistical models and machine learning techniques to identify individuals at risk of developing specific diseases before clinical onset, enabling early intervention through data-driven risk stratification and personalized prevention strategies.

89

Publications

5.2K

Citations

661

Authors

245

Institutions

Publications per year

2017–2026

64

Authors

661

  1. VC
    Vincenzo Costigliola

    University of Bonn, Germany

    4 publications · 119 citations

    4

    h-index

  2. OG
    Olga Golubnitschaja

    University of Bonn, Germany

    4 publications · 119 citations

    4

    h-index

  3. HŌ
    Hiroshi Ōyama

    The University of Tokyo, Japan

    2 publications · 36 citations

    2

    h-index

  4. DI
    Daisuke Ichikawa

    St. Marianna University School of Medicine, Japan

    2 publications · 36 citations

    2

    h-index

  5. NC
    Nimai Chand Das Adhikari

    Indian Institute of Space Science and Technology, India

    1 publications · 21 citations

    1

    h-index

1–5 of 661

Venues

  1. The EPMA Journal

    4 publications · 119 citations

    4

    h-index

  2. International Journal of Medical Informatics

    2 publications · 61 citations

    2

    h-index

  3. Journal of Medical Internet Research

    2 publications · 46 citations

    2

    h-index

  4. PLoS ONE

    2 publications · 1.5K citations

    2

    h-index

  5. Procedia Computer Science

    2 publications · 359 citations

    2

    h-index

1–5