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Large-Scale Data Mining of Rapid Residue Detection Assay Data From HTML and PDF Documents: Improving Data Access and
Majid Jaberi-Douraki1,2,3, Soudabeh Taghian Dinani1,3,4, Nuwan Indika Millagaha Gedara1,3,5
1DATA Consortium, www.1DATA.life, Olathe, KS, United States.
Artificial intelligence (AI) extracts crucial rapid assay data for drug residues in food animals. This ensures accurate monitoring for human health protection and compliance with regulations.
Area of Science:
- Veterinary Pharmacology and Toxicology
- Data Science and Artificial Intelligence
- Food Safety Assurance
Background:
- Extra-label drug use in food animals necessitates accurate withdrawal intervals based on pharmacokinetic data.
- Paucity of data or large-scale treatments drive the need for rapid drug residue testing to protect human health.
- Commercial rapid assay test data, often found in inaccessible documents, requires efficient extraction and correlation with FDA tolerances.
Purpose of the Study:
- To develop and evaluate an AI-driven data-mining method for automatically extracting rapid assay data from electronic documents.
- To create a real-time system for reflowing document content for accessibility and research data mining.
- To provide veterinarians and producers with an accessible online interface for interactive searching of assay parameters against FDA-approved tolerances.
Main Methods:
- Developed an automatic electronic data extraction method using a software module, pattern recognition tool, and data mining engine.
- Utilized AI technology for text extraction and mining to convert embedded information into structured formats.
- Created a real-time conversion system for reflowing document content.
Main Results:
- Successfully developed and evaluated an AI-based data-mining method for extracting rapid assay data.
- Enabled real-time conversion and reflowing of electronic document content for improved accessibility.
- Provided an online interface for interactive searching of commercial test assay parameters against FDA tolerances.
Conclusions:
- AI-powered data mining offers an efficient solution for extracting and managing critical drug residue assay information.
- The developed system enhances accessibility and usability of vital data for veterinarians and producers.
- This approach supports informed decision-making in food animal medicine and ensures adherence to safety standards.
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