DICE: A Drug Indication Classification and Encyclopedia for AI-Based Indication Extraction.

ABSTRACT: Drug labeling contains an 'INDICATIONS AND USAGE' that provides vital information to support clinical decision making and regulatory management. Effective extraction of drug indication information from free-text based resources could facilitate drug repositioning projects and help collect real-world evidence in support of secondary use of approved medicines. To enable AI-powered language models for the extraction of drug indication information, we used manual reading and curation to develop a Drug Indication Classification and Encyclopedia (DICE) based on FDA approved human prescription drug labeling. A DICE scheme with 7,231 sentences categorized into five classes (indications, contradictions, side effects, usage instructions, and clinical observations) was dev

SUBMITTER: Bhatt A 

PROVIDER: S-EPMC8366025 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature