Artificial intelligence is being used by life science organizations to accelerate drug development and spur medical device innovation by through genomic profiling, recognizing a need for immediate clinical intervention, and by monitoring medication adherence. In this track, we will explore key machine learning and drug development insights for utilizing AI in clinical development.
Track Chair Karim Damji, Senior Vice President of Product Marketing, SAAMA TECHNOLOGIES INC
While applications, systems, and platforms have been developed to transform healthcare innovation and delivery, there is lacking narrative in AI’s actual execution in healthcare organizations. In this track, healthcare and technology experts showcase AI applications to improve health outcomes, prevent diseases, streamline diagnoses, and much more.
Track Chair James Fackler, M.D., Director, Pediatric Critical Care Medicine Fellowship; Associate Professor of Anesthiology and Critical Care Medicine, JOHNS HOPKINS MEDICINE
The mission of this track is to balance the practical discussions with forward-thinking conversation. Experts in blockchain-based systems, IoT, and other future technologies will provide insights into the technological advancements on the horizon and how life science and healthcare organizations can prepare their business and data.
Track Chair Evon Holladay, Analytics Executive in Residence, UNIVERSITY OF DENVER
Top Five Reasons to Attend
Define standards for the ethics, law, and practice of machine learning and privacy in the healthcare and life science industries
Examine AI, reimbursement schemes and integrated healthcare services to understand privacy, data protection, and data ownership
Use adversarial and variational autoencoders for generating new molecular structures
Implement a cutting-edge health data strategy while maintaining compliance with complex privacy and security regulatory frameworks
Outline issues, roadblocks, and bottlenecks in the current drug discovery process that can be hurdled with AI technologies