The Bottom Line: Deep Learning and AI Pipelines for Biotechnology & Healthcare

Abstract: The goal of this session is to demonstrate and learn about building end-to-end pipelines for biotechnology and healthcare applications. Artificial intelligence is poised to make radical changes in healthcare, transforming areas such as diagnosis, medical imaging, genomics, and drug discovery. Pragmatic technical implementation can have the potential to lower costs, identify more effective treatments, develop new tools and products, while driving company growth through automation and competitive advantage. In this session we will describe: The significance of data-strategy and its impact on core business goals; case studies exploring the business value and impact of transforming divisions with AI-driven methods employing deep learning; and how the final AI-framework is integrated into a company‚Äôs internal workflow. We highly encourage executives and leaders of all backgrounds to join (no AI/healthcare background necessary).

Bio: Alexander Tolpygo is the President & COO of SFL Scientific, a data science consulting firm that specializes in solving complex data, automation, and R&D problems. His firm develops, integrates, and manages sophisticated Artificial Intelligence systems by leveraging emerging technologies in data engineering, deep learning, and predictive analytics. A biomedical engineer and statistician by training, his experience spans multiple industries including healthcare, biotech, pharmaceuticals, medical devices, insurance, and manufacturing. He helps business leaders narrow the gap in development, identifying where digital transformation and big data can accelerate the accurate decisions that lead to innovation and revenue growth.