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
Parents
22
Context-Aware Visual Compatibility Prediction
Guillem Cucurull, Perouz Taslakian, David Vázquez · 2019 · 114 citations
Fashion Outfit Complementary Item Retrieval
Yen-Liang Lin, Son N. Tran, Larry S. Davis · 2020 · 89 citations
Learning Similarity Conditions Without Explicit Supervision
Reuben Tan, Mariya I. Vasileva, Kate Saenko et al. · 2019 · 87 citations
1–5 of 22
67
University of Illinois Urbana-Champaign, United States
4 publications · 170 citations
4
h-index
3
h-index
2
h-index
2
h-index
2
h-index
1–5 of 67
30
Amazon (Germany)
Berlin, Germany
3 h-index
17 publications
673 citations
Tianjin University
Tianjin, China
2 h-index
9 publications
205 citations
Shandong University of Science and Technology
Qingdao, China
2 h-index
2 publications
46 citations
Purdue University West Lafayette
West Lafayette, United States
2 h-index
2 publications
58 citations
University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
7 publications
237 citations

Chinese Academy of Sciences
Beijing, China
1 h-index
5 publications
555 citations
Northwest A&F University
Yangling, China
1 h-index
3 publications
66 citations
National University of Singapore
Singapore, Singapore
1 h-index
1 publications
36 citations
1–8 of 30
2 publications · 46 citations
2
h-index
Repository · 2 publications · 40 citations
2
h-index
1 publications · 39 citations
1
h-index
1 publications · 54 citations
1
h-index
1 publications · 36 citations
1
h-index
1–5