Drug Interaction Machine Learning

Drug Interaction Machine Learning is a computational methodology that employs machine learning techniques to predict, analyze, or characterize interactions between drugs by modeling pharmacological, biological, or clinical data within the domain of drug-drug interaction informatics.

101

Publications

5.8K

Citations

440

Authors

224

Institutions

Publications per year

2017–2026

84

Authors

440

  1. LC
    Lei Chen

    Shanghai Maritime University, China

    5 publications · 227 citations

    5

    h-index

  2. NQ
    Nguyen Quoc Khanh Le

    Taipei Medical University, Taiwan

    5 publications · 365 citations

    4

    h-index

  3. YC
    Yu‐Dong Cai

    Shanghai University, China

    3 publications · 116 citations

    3

    h-index

  4. YQ
    Yang Qiu

    Huazhong Agricultural University, China

    3 publications · 580 citations

    3

    h-index

  5. TH
    Tao Huang

    Shanghai Institutes for Biological Sciences, China

    3 publications · 181 citations

    3

    h-index

1–5 of 440

Venues

  1. BMC Bioinformatics

    9 publications · 451 citations

    9

    h-index

  2. Briefings in Bioinformatics

    6 publications · 550 citations

    6

    h-index

  3. Scientific Reports

    6 publications · 486 citations

    6

    h-index

  4. PLoS ONE

    3 publications · 177 citations

    3

    h-index

  5. 3

    h-index

1–5