Why enroll

Data scientists, healthcare professionals, and technology innovators should watch this seminar to understand the future of "Digital Enablement" in complex medical environments. Dr. Jaffray provides a roadmap for moving beyond simple data analytics to building robust "Learning Machines" that handle high-velocity, high-variety clinical data. By watching, participants will gain unique insights into the intersection of AI, blockchain-based data governance, and patient-centered consent, offering a practical perspective on how to overcome the administrative and ethical bottlenecks that currently stall medical research and innovation.

Is this seminar for you?

You should take this if

You work in Medical Instruments
You're a Data Science & Analysis professional
You have some foundational knowledge in the subject
You want to build skills in Artificial Intelligent, Business Analysis

You should skip if

You're looking for an introductory overview seminar
You need a different specialisation outside Data Science & Analysis
You need live interaction with an instructor

Seminar details

This Seminar features a keynote presentation by Dr. David Jaffray, the Chief Technology and Digital Officer at MD Anderson Cancer Center, during the 2019 Data Science Conference at Rice University. Dr. Jaffray outlines a transformative vision for a "Learning Health System," where digital architecture and data science are integrated to learn from every patient encounter to improve future care. The talk addresses the shift from static "Big Data" to continuous data flows, the challenges of data veracity in healthcare, and the critical role of automated digital alignment in making cancer history.

Source: Rice Ken Kennedy Institute [Youtube]

Seminar suitable for

Key topics covered

- Introduction

- The Learning Health System Paradigm

- Overcoming Human Cognitive Capacity

- Data Governance & Culture

- Blockchain for Patient Consent

- The Future of Automated Science

Course content

The course is readily available, allowing learners to start and complete it at their own pace.

1 lectures50 min

Data Science Conference - David Jaffray
50 min

Opportunities that await you!

Skills & tools you'll gain

Artificial Intelligent

Business Analysis

Career opportunities

Why people choose EveryEng

Industry-aligned seminars, expert training, hands-on learning, recognized certifications, and job opportunities-all in a flexible and supportive environment.

What attendees say about this seminar

Talari Pravallika

Sep 29, 2026

Bhavani S Student

Feb 22, 2026

Nice

Engineering Academy Engineer

Feb 7, 2026

Nice Explanation

Rohini Aware

Feb 25, 2026

Coming into this course, I had some prior exposure to the subject, mainly through hand calcs and a bit of older STAAD versions, but the Connect Edition interface was a gap for me. The walkthrough on creating models, defining beam vs plate elements, and setting proper support conditions helped clear that up. What stood out was applying load combinations correctly and actually seeing how changes affected analysis results. From a railtransport angle, the sections where I could map axle loads from rail bridges into STAAD models were immediately useful. Understanding how to idealize rail bridge load cases and account for ballast and sleeper load distribution made the software feel relevant to real rail jobs, not just textbook frames. Track alignment constraints aren’t modeled directly, but the discussion helped frame assumptions better. One challenge was getting comfortable with local vs global axes when assigning loads; a couple of early models gave odd reactions until that clicked. A practical takeaway is a simple modeling checklist—define geometry, verify units, apply loads, then sanity-check reactions before design. That’s already saving time on small bridge assessments. It definitely strengthened my technical clarity.

Data Science Conference - David Jaffray