Over two days, the Ai4 Healthcare conference brings together business leaders and data practitioners to facilitate the adoption of artificial intelligence and machine learning technologies.
With a use-case oriented approach to content, our goal is to deliver actionable insights from those working on the frontlines of AI in the enterprise. We try to provide a common framework for thinking about what AI means to the healthcare industry and to deliver content that progresses understanding at any stage of an organization’s AI journey. Welcome to our community!
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Over two days, the Ai4 Healthcare conference brings together business leaders and data practitioners to facilitate the adoption of artificial intelligence and machine learning technologies.
With a use-case oriented approach to content, our goal is to deliver actionable insights from those working on the frontlines of AI in the enterprise. We trie to provide a common framework for thinking about what AI means to the financial services industry and to deliver content that progresses understanding at any stage of an organization’s AI journey. Welcome to our community!
 AI FOCUSED |
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| HEALTHCARE SPECIFIC |
| APPLICATION ONLY |
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| USE CASE DRIVEN |
Hear top use cases for AI in healthcare. Presentations range from high level insights to highly specific solutions. We focus on covering the industry’s most pressing problems through use cases from business execs and technical leaders who have solved them. See below for a diagram of topics covered.
2 DAYSEvery major application of AI in healthcare will be covered. |
40+ TALKSSpeakers from the world’s largest healthcare companies and from cutting edge startups will take stage. |
2 TRACKSExplore the specifics behind the model in a technical talk or the business implications in a non-technical talk. |
20+ HOURS OF CONTENTYou’ll have plenty of choices to make sure you’re learning what you need. |
Hear top use cases for AI in healthcare. Presentations range from high level insights to highly specific solutions. We focus on covering the industry’s most pressing problems through use cases from business execs and technical leaders who have solved them. See below for a diagram of topics covered.
2 DAYSEvery major application of AI in healthcare will be covered. |
|
40+ TALKSSpeakers from the world’s largest healthcare companies and from cutting edge startups will take stage. |
|
2 TRACKSExplore the specifics behind the model in a technical talk or the business implications in a non-technical talk. |
|
20+ HOURS OF CONTENTYou’ll have plenty of choices to make sure you’re learning what you need. |
This year, we’re offering two distinct tracks to differentiate between technical and non-technical discussions. See below to determine which track best fits your interests and goals.
Both tracks will cover all topics listed above either from the perspective of the business exec (Business Track) or data practitioner (Data Track).
| TRACK 1 | TRACK 2 |
DATA TRACKThis track was designed for our technical audience. You can expect a deep dive into the specifics of the machine learning models. Most talks during this track will be in a longer 50-minute format. Hear topics including:
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BUSINESS TRACKThis track was designed for attendees holding non-technical and hybrid job functions seeking to understand the business value of specific AI projects. Most talks during this track will be in a 30-minute format. No technical expertise required. Hear topics including:
|
This year, we’re offering two distinct tracks to differentiate between technical and non-technical discussions. See below to determine which track best fits your interests and goals.
Both tracks will cover all topics listed above either from the perspective of the business exec (Business Track) or data practitioner (Data Track).
| TRACK 1 |
DATA TRACKThis track was designed for our technical audience. You can expect a deep dive into the specifics of the machine learning models. Most talks during this track will be in a longer 50-minute format. Hear topics including:
|
| TRACK 2 |
BUSINESS TRACKThis track was designed for attendees holding non-technical and hybrid job functions seeking to understand the business value of specific AI projects. Most talks during this track will be in a 30-minute format. No technical expertise required. Hear topics including:
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Make connections with people who can help. As attendance is by application only, we maintain low rates of service providers to reduce sales pitches and increase quality dialogue. Use our mobile networking app to connect with other conference attendees through 1:1 meeting scheduling. Click here to download the 2018 attendee list.
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2018 Included Attendees From…
Make connections with people who can help. As attendance is by application only, we maintain low rates of service providers to reduce sales pitches and increase quality dialogue. Use our mobile networking app to connect with other conference attendees through 1:1 meeting scheduling. Click here to download the 2018 attendee list.
|
|
2018 Included Attendees From…
Ai4 Healthcare welcomes 45+ speakers over the two days. See below for confirmed speakers.
Nels Lindahl
Emma Yamada
Jim Weatherall
Gloria Marcia
Christopher Khoury
Hakima Ibaroudene
Georgios Ouzounis
Anthony Chang
Satish Swargam
Daniel Chertok
Shivpratap Singh
Punit Soni
Ai4 Healthcare welcomes 40+ speakers over the two days. See below for a snapshot of our speaker lineup from last year.
Our first speaker announcement will be Q2 of 2019.
Hod Lipson
Talk Title: Opening Keynote: The Six Waves of AI
Peter Fleischut, M.D.
Panel Title: Hospital-Wide AI Transformation
Melanie Kambadur, Ph.D.
Talk Title: Finding Structure in Noisy Claims and Member Messages
Dmitriy Gorenshteyn, Ph.D.
Talk Title: Building Clinically Relevant Models
Sean Lane
Panel Title: Hospital-Wide AI Transformation
David Tsay, M.D., Ph.D.
Panel Title: Hospital-Wide AI Transformation
Robbie Freeman
Panel Title: Hospital-Wide AI Transformation
Yindalon Aphinyanaphongs, M.D., Ph.D.
Talk Title: Principles for Translating Predictive Models Into Clinical Practice
Nikhil Krishnan
Talk Title: What The Tech Giants Are Doing In Healthcare
Nick Patyon
Talk Title: Lessons for an Enterprise Approach to Modeling at Scale
Jeff Goldsmith
Talk Title: Functional Data Methods for Wearable Device Data
Sasha Gutfraind, Ph.D.
Talk Title: Saving Patient Ryan 2.0: Machine Learning-Driven Identification, Prediction and Prevention of High Cost Patients
Sandy Balkin
Talk Title: Demonstrating Commercial RWE Value Through A Proof of Concept Machine Learning Predictive Segmentation Model
Sara Aby, Ph.d.
Talk Title: AI in Healthcare Marketing: A New Data Frontier
Kenrick Cato, RN, Ph.D.
Talk Title: Predictive Analytics Leveraging Healthcare Process Models of Clinical Concern (HPM-CC): The CONCERN Study
Sarah Collins, RN, Ph.D.
Talk Title: Predictive Analytics Leveraging Healthcare Process Models of Clinical Concern (HPM-CC): The CONCERN Study
Sheetal Sood
Talk Title: Automating Information Governance: Is AI The Key?
Parsa Mirhaji MD, Ph.D.
Panel Title: Patient-Centered Analytical Learning Machine: An Enterprise Vision for Digital Transformation and Large Scale Adoption of AI and Machine Learning in Healthcare and Life Sciences
Andy Merrill
Talk Title: Opening Keynote: Adopting AI Capabilities? Lessons From the Front Lines
Madhuri Sebastian
Talk Title: AI in Healthcare Imaging - Opportunities and Challenges
Rajeev Ronanki
Panel Title: Population Health: A Data-Driven Model for Patient Care
Jodie Gillon
Panel Title: Leveraging AI For Diagnosis
Vish Anantraman
Panel Title: Population Health: A Data-Driven Model For Patient Care
Michael Recht
Talk Title: AI in Radiology: Threat or Opportunity?
Emmanuel Fombu
Talk Title: The Future of Healthcare: Humans and Machines Partnering for Better Outcomes
Viraj Patwardhan
Talk Title: Smart Patient Room Concierge
Jesse Bridgewater
Panel Title: Population Health: A Data-Driven Model For Patient Care
Esteban Rubens
Talk Title: Infrastructure Matters: Bringing Deep Learning to Enterprise Imaging Clinical Practice
Susan Abedi
Panel Title: Leveraging AI For Diagnosis
Michael Frank
Talk Title: Machine Learning to Boost R&D Productivity in Pharma
Christopher Lehmuth
Talk Title: Breaking the Cycle: Moving From Issue Management to Prevention with Predictive Analytics
Len Usvyat, Ph.D.
Talk Title: Applying Data Science to Understand and Improve Quality of Life in Patients with Chronic Disease
Isabelle Lousada
Panel Title: Leveraging AI For Diagnosis
Michelle Stansbury
Talk Title: Creating A Digital Workforce: Implementing Intelligent Automation in Hospital Operations
Christopher Steel
Talk Title: Building Business Value: Using AI and Machine Learning to Reduce Costs, Increase Revenue, and Drive Competitive Differentiation
Vishaal Virani, M.D.
Talk Title: How Chatbots Will Positively Transform Care for Patients
Michael Berger
Talk Title: Decision-Centricity: Operationalizing Analytics and Data Science in Health Systems
Sanji Fernando
Panel Title: Population Health: A Data-Driven Model for Patient Care
Bülent Kiziltan Ph.D.
Talk Title: Creating Value With AI
Erik Pupo
Panel Title: Population Health: A Data-Driven Model for Patient Care
Adam Jenkins
Talk Title: Real World Issues During Implementing AI In The Healthcare System
Pamila Brar
Panel Title: Transforming Prevention through AI
John Fahrenbach
Talk Title: Augmenting Hospital Operations with AI
Mark Kanner, Ph.D.
Talk Title: How AI Can Help in Making Our Healthcare System More Efficient
Tawnya Infantino
Talk Title: Leveraging AI & ML To Empower and Engage Your Patients
Convene, 117 W 46th Street, New York, NY 10036
This brand new venue is located conveniently in Midtown West, featuring close proximity to major transpiration hubs, Times Square, and Rockefeller Center.
Convene, 117 W 46th Street, New York, NY 10036
This brand new venue is located conveniently in Midtown West, featuring close proximity to major transpiration hubs, Times Square, and Rockefeller Center.