Dataset Open Access
Extracting interpretable rules with Bayesian Networks. A case study of intrinsic human hazardous properties of silver nanoforms for the Safety Dimension of Safe and Sustainable by design paradigm.
Irini Furxhi
Three different datasets: toxicological attributes in i) lung and ii) intestinal cell line along with system dependent features and iii) system independent pchem properties) were merged. Each row represents one set of experimental testing conditions and related system dependent nanodescriptors based on the exposure dose and NFs pre-treatment (for intestinal assessments). The system independent inputs are NF specific and independent of experimental conditions. Data is captured via FAIR principles where the reader can find the origin (institution) of each data, the responsible data creators (experimentalists), the raw measurements, the protocols followed and the instrumentations used for each experiment. .
| Name | Size | |
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Supplementary Material_FAIR data.xlsx
md5:bfb24a2f79670082c0132fdecf3afd0c |
659.8 kB | Download |
| All versions | This version | |
|---|---|---|
| Views | 19 | 19 |
| Downloads | 8 | 8 |
| Data volume | 5.3 MB | 5.3 MB |
| Unique views | 17 | 17 |
| Unique downloads | 8 | 8 |
- Publication date:
- November 18, 2022
- DOI:
-
- Keyword(s):
- SSbD, nanoforms, machine learning
- Grants:
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European Commission:
- ASINA - Anticipating Safety Issues at the Design Stage of NAno Product Development (862444)
- License (for files):
- Creative Commons Attribution 4.0 International