Life Science organizations face the challenge of extracting valuable data from vast amounts of documents for current and future projects, and business insights. It can hinder decision-making and delay critical research advancements and product developments.
This webinar offers actionable insights from a real case study. It highlights how to set up a data pipeline that extracts and transforms data from clinical trial studies without the need for coding expertise.
Key Takeaways:
- How to overcome challenges associated with extracting insights from a high volume of complex documents?
- What are the potential cost-saving opportunities associated with leveraging AI data extraction technology in Life Sciences research and development?
- How "Human-in-the-Loop" designs ensure data accuracy, reliability, and consistency when extracting insights from large volumes of documents?
- What practical steps to take in order to integrate AI data extraction solutions into existing workflows and processes effectively?
Agenda:
- 5 min - Welcome and Introduction (Martin Keller, CEO of ACODIS)
- 15 min - Business Impact and Key Challenges and Learnings of extracting data from unstructured sources (Dr. Shannon Montgomery, Data Scientist, CAPGEMINI ENGINEERING)
- 15 min - How to scale and extract high-quality data with AI-powered solution? (Martin Keller, CEO of ACODIS)
- 10 min - Q&A