Expectation-Maximization Model for Substitution of Missing Values Characterizing Greenness of Organic Solvents - Publication - Bridge of Knowledge

Search

Expectation-Maximization Model for Substitution of Missing Values Characterizing Greenness of Organic Solvents

Abstract

Organic solvents are ubiquitous in chemical laboratories and the Green Chemistry trend forces their detailed assessments in terms of greenness. Unfortunately, some of them are not fully characterized, especially in terms of toxicological endpoints that are time consuming and expensive to be determined. Missing values in the datasets are serious obstacles, as they prevent the full greenness characterization of chemicals. A featured method to deal with this problem is the application of Expectation-Maximization algorithm. In this study, the dataset consists of 155 solvents that are characterized by 13 variables is treated with Expectation-Maximization algorithm to predict missing data for toxicological endpoints, bioavailability, and biodegradability data. The approach may be particularly useful for substitution of missing values of environmental, health, and safety parameters of new solvents. The presented approach has high potential to deal with missing values, while assessing environmental, health, and safety parameters of other chemicals.

Citations

  • 9

    CrossRef

  • 0

    Web of Science

  • 7

    Scopus

Authors (4)

Cite as

Full text

download paper
downloaded 29 times
Publication version
Accepted or Published Version
DOI:
Digital Object Identifier (open in new tab) 10.3390/molecules23061292
License
Creative Commons: CC-BY open in new tab

Keywords

Details

Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
MOLECULES no. 23, edition 6, pages 1292 - 1300,
ISSN: 1420-3049
Language:
English
Publication year:
2018
Bibliographic description:
Łuczyńska G., Pena-Pereira F., Tobiszewski M., Namieśnik J.: Expectation-Maximization Model for Substitution of Missing Values Characterizing Greenness of Organic Solvents// MOLECULES. -Vol. 23, iss. 6 (2018), s.1292-1300
DOI:
Digital Object Identifier (open in new tab) 10.3390/molecules23061292
Verified by:
Gdańsk University of Technology

seen 130 times

Recommended for you

Meta Tags