Compatibility Prediction Models

Compatibility Prediction Models is a computational framework that systematically integrates physicochemical, pharmacological, and clinical data to predict the stability and safety of co-administered drugs, distinguishing it from general drug interaction tools by focusing specifically on physicochemical compatibility and therapeutic co-administration outcomes.

22

Publications

883

Citations

67

Authors

30

Institutions

Publications per year

2017–2026

17

Authors

67

  1. MI
    Mariya I. Vasileva

    University of Illinois Urbana-Champaign, United States

    4 publications · 170 citations

    4

    h-index

  2. YL
    Yen-Liang Lin

    National Taiwan University, Taiwan

    3 publications · 147 citations

    3

    h-index

  3. PJ
    Peiguang Jing

    Tianjin University, China

    2 publications · 46 citations

    2

    h-index

  4. RS
    Rohan Sarkar

    Purdue University West Lafayette, United States

    2 publications · 58 citations

    2

    h-index

  5. YS
    Yuting Su

    Tianjin University, China

    2 publications · 46 citations

    2

    h-index

1–5 of 67

Venues

  1. IEEE Transactions on Multimedia

    2 publications · 46 citations

    2

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 40 citations

    2

    h-index

  3. Journal of Social and Clinical Psychology

    1 publications · 39 citations

    1

    h-index

  4. Materials & Design

    1 publications · 54 citations

    1

    h-index

  5. 1

    h-index

1–5