Daniel Holewienko
Executive Director, Big Data and Business Intelligence Henry ScheinDaniel Holewienko is a 20+ year experienced Technology Executive in the Healthcare, Financial Services, Media, Education, and Retail industries. He started his career in software development and later focused on overall Technology Strategy, Transformation, and Management in mid to large-size regional and global organizations. Along the way, Dan has held Director, Managing Director, Executive Director, VP, CTO, and CIO titles at firms such as Seiko, CIT Group, WNET-Channel Thirteen, Lord Abbett & Co, Kaplan, Northwell Health, Marlabs, and Henry Schein. He has also been contracted to coach and direct IT and business executives in technology transformation and strategy in such firms as Practising Law Institute, Mizuho Securities, Univision, Roundabout Theater, AppNexus, International Rescue Committee, Ryder, and other brand names clients as Managing Direct of TBT Management Consulting.
Dan is presently the Executive Director, Big Data and Business Intelligence at Henry Schein, where he has boot-strapped their Big Data program to consolidate internal and external data globally and use advanced ML & AI technologies, data science, and analytics to create higher customer value and new business opportunities.
Dan is an active member of the New York Chapter CTO Club and author of numerous industry articles. He has been a guest speaker, panelist, and moderator at dozens of user groups and conferences throughout his career. Dan holds a BA from CUNY and several management and tech-related accreditations/certifications.
ABSTRACT
The Key Elements of Successful ML/AI in Healthcare
ML/AI has gained significant adoption in healthcare in the last 5 years and continues to provide opportunities for new and innovative services as well as optimized traditional services. Additionally, ML/AI is offering competitive advantage in healthcare. Faster, more accurate diagnosis… More complete and diverse treatments… Better therapy planning… New predictive/preventive care… Improved drug discovery… Streamlined healthcare workflows… Improved clinical resource management… The list goes on… So, to remain competitive healthcare orgs must partake in ML/AI. However, many struggle to bootstrap their ML/AI initiatives due to high-complexity, high-cost, inadequate tech foundation, and inadequate staff/skills. And statistically the failure rate of ML/AI’s projects is close to 85%. So, what should healthcare orgs do?
This session will explore the healthcare ML/AI landscape, note adoption/successes/failures, point out the Elements REQUIRED to secure ML/AI success, and deep dive into a Use-Case with its developers that leveraged these elements to produce Healthcare Value.
The discussion will be led by Dan Holewienko, Executive Director, Big Data & Business Intelligence for Henry Schein. Joining him will be two colleagues from Artha Solutions LLC, who specializes in Data Science and ML/AI implementations in the Healthcare domain:
- Emmanuel Egbo, Management Consultant, Healthcare Analytics, Artha Solutions LLC
- Akhil Alluri, Data Science Consultant Artha Solutions LLC