Daniel Holewienko

Daniel 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 Managing Director, Executive Director, Director, VP, CTO, and CIO titles at firms such as Seiko, CIT Group, WNET-Channel Thirteen, Lord Abbett & Co, Kaplan, Northwell Health System, Marlabs, and Henry Schein. He has also been contracted to coach and directed 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 is boot-strapping their Big Data program to consolidate internal and external data globally and use advanced ML & AI technologies, data science, and advance 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 Power of Low-Code / Pre-Trained ML in Healthcare

Ai / ML has gained significant adoption in Healthcare in the last 5 years and continues to provide opportunities for new, innovative services as well as the optimization of existing services. Ai / ML has becoming a 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… The list goes on… However, many small / mid-sized Healthcare organization struggle to bootstrap their Ai / ML initiatives due to Ai/ML’s high project failure rates, high-complexity, high-cost, inadequate tech foundation, and inadequate staff/skills to make it viable.

This session will explore this dilemma and posit The Power of Low-Code / Pre-Trained ML in Healthcare and how it can be used to:
1. Ramp-up quickly to “Get in the ML Game”
2. Avoid many of the pitfalls of inadequate Tech Foundations and Staffing
3. Reduce the Tech Complexities and Cost and remain Focused on outcomes
4. Form a virtual team with the skills needed to build, delivery, and support ML driven Healthcare offerings

This session will be led by Dan Holewienko, Executive Director, Big Data & Business Intelligence for Henry Schein. Joining him will be two colleagues from ElectrifAi, LLC, who specializes in helping company rapidly adopt Ai through the use of its Data Scientists and Low-Code ML, Pre-Trained / Pre-Built ML models.
- Dr. Dmitry Pavlov, Senior Data Scientist
- Nancy Hornberger, EVP of Healthcare.