A machine learning driven automated system for safety data sheet indexing.

ABSTRACT: Safety Data Sheets (SDS) are foundational to chemical management systems and are used in a wide variety of applications such as green chemistry, industrial hygiene, and regulatory compliance, among others within the Environment, Health, and Safety (EHS) and the Environment, Social, and Governance (ESG) domains. Companies usually prefer to have key pieces of information extracted from these datasheets and stored in an easy to access structured repository. This process is referred to as SDS "indexing". Historically, SDS indexing has always been done manually, which is labor-intensive, time-consuming, and costly. In this paper, we present an automated system to index the composition information of chemical products from SDS documents using a multi-stage ensemble method with a combination of m

SUBMITTER: Suman A 

PROVIDER: S-EPMC10883951 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature