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!                     

     AI FOCUSED

     APPLICATION ONLY

     HEALTHCARE SPECIFIC 

     USE CASE DRIVEN

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

     HEALTHCARE SPECIFIC 

     APPLICATION ONLY

     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 DAYS                                 

Every major application of AI in healthcare will be covered.

40+ TALKS

Speakers from the world’s largest healthcare companies and from cutting edge startups will take stage.

2 TRACKS

Explore the specifics behind the model in a technical talk or the business implications in a non-technical talk.

20+ HOURS OF CONTENT

You’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 DAYS 

Every major application of AI in healthcare will be covered.

40+ TALKS

Speakers from the world’s largest healthcare companies and from cutting edge startups will take stage.

2 TRACKS

Explore the specifics behind the model in a technical talk or the business implications in a non-technical talk.

20+ HOURS OF CONTENT

You’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 TRACK

This 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:

  • Scaling to Big Data
  • Model Interpretability
  • Data Privacy and Security
  • Dealing with Biased Data Sets
  • Productionizing Your Model
  • Cloud v Local Environment
  • Unstructured Data
  • Deep Learning
  • Dealing with Legacy Systems
  • Reinforcement Learning
  • And More!

BUSINESS TRACK

This 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:

  • Understanding AI Capabilities
  • Top Use Cases For AI & ML
  • Scoping Your Project
  • Automation vs Augmentation
  • Compliance & AI
  • Infrastructure Needs
  • Building vs Buying
  • Pilot Programs & Proof of Concept
  • Building Your Data Science Team
  • ROI & Measuring Success
  • And More!

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 TRACK

This 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:

  • Scaling to Big Data
  • Model Interpretability
  • Data Privacy and Security
  • Dealing with Biased Data Sets
  • Productionizing Your Model
  • Cloud v Local Environment
  • Unstructured Data
  • Deep Learning
  • Dealing with Legacy Systems
  • Reinforcement Learning
  • And More!
TRACK 2                            

BUSINESS TRACK

This 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:

  • Understanding AI Capabilities
  • Top Use Cases For AI & ML
  • Scoping Your Project
  • Automation vs Augmentation
  • Compliance & AI
  • Infrastructure Needs
  • Building vs Buying
  • Pilot Programs & Proof of Concept
  • Building Your Data Science Team
  • ROI & Measuring Success
  • And More!

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.

     1:1 MEETING SCHEDULING                             

      EXECUTIVE LEVEL CONNECTIONS                                    

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.

 1:1 MEETING SCHEDULING

 EXECUTIVE CONNECTIONS

2018 Included Attendees From…

Ai4 Healthcare welcomes 45+ speakers over the two days. See below for confirmed speakers.

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Nels Lindahl

Director - Clinical Decision Systems, CVS Health
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Emma Yamada

Director of Data Science, Holy Name Medical Center
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Jim Weatherall

Vice President of Data Science & AI, R&D BioPharmaceuticals, AstraZeneca
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Gloria Marcia

Data Scientist, Roche AG
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Christopher Khoury

Vice President - Environmental Intelligence & Strategic Analytics, American Medical Association
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Hakima Ibaroudene

Group Leader - Research & Development, Southwest Research Institute
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Georgios Ouzounis

Senior Computer Vision Engineer, Arlo Technologies
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Anthony Chang

Chief Intelligence and Innovation Officer, Children's Hospital of Orange County
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Satish Swargam

Lead Security Architect, Cerner
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Daniel Chertok

Senior Data Scientist, Northshore
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Shivpratap Singh

Senior Advisor, CVS Caremark
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Punit Soni

Co-founder & CEO, Suki
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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.

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Hod Lipson

Professor of Engineering and Data Science, Columbia University

Talk Title: Opening Keynote: The Six Waves of AI

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Peter Fleischut, M.D.

SVP & Chief Transformation Officer, NewYork-Presbyterian

Panel Title: Hospital-Wide AI Transformation

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Melanie Kambadur, Ph.D.

Search Engineering Team Lead, Oscar Insurance

Talk Title: Finding Structure in Noisy Claims and Member Messages

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Dmitriy Gorenshteyn, Ph.D.

Lead Data Scientist, Memorial Sloan Kettering

Talk Title: Building Clinically Relevant Models

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Sean Lane

Co-Founder and CEO, Olive

Panel Title: Hospital-Wide AI Transformation

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David Tsay, M.D., Ph.D.

Associate Chief Transformation Officer, NewYork-Presbyterian

Panel Title: Hospital-Wide AI Transformation

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Robbie Freeman

Senior Director Clinical Operations, Mount Sinai

Panel Title: Hospital-Wide AI Transformation

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Yindalon Aphinyanaphongs, M.D., Ph.D.

Director of Clinical Predictive Analytics in the Center for Health Innovations, NYU Langone Health

Talk Title: Principles for Translating Predictive Models Into Clinical Practice

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Nikhil Krishnan

Senior Analyst, CB Insights

Talk Title: What The Tech Giants Are Doing In Healthcare

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Nick Patyon

Head of Marketing & Partnerships, SigOpt

Talk Title: Lessons for an Enterprise Approach to Modeling at Scale

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Jeff Goldsmith

Associate Professor in Biostatistics, Columbia University Mailman School of Public Health

Talk Title: Functional Data Methods for Wearable Device Data

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Sasha Gutfraind, Ph.D.

Senior Healthcare Data Scientist, Blue Health Intelligence

Talk Title: Saving Patient Ryan 2.0: Machine Learning-Driven Identification, Prediction and Prevention of High Cost Patients

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Sandy Balkin

Head of Integrated Insights & Platforms, Sanofi

Talk Title: Demonstrating Commercial RWE Value Through A Proof of Concept Machine Learning Predictive Segmentation Model

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Sara Aby, Ph.d.

Senior Data Scientist, Crossix

Talk Title: AI in Healthcare Marketing: A New Data Frontier

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Kenrick Cato, RN, Ph.D.

Nurse Researcher and Assistant Professor, NewYork-Presbyterian Hospital and Columbia University

Talk Title: Predictive Analytics Leveraging Healthcare Process Models of Clinical Concern (HPM-CC): The CONCERN Study

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Sarah Collins, RN, Ph.D.

Assistant Professor of Biomedical Informatics and Nursing, Columbia University

Talk Title: Predictive Analytics Leveraging Healthcare Process Models of Clinical Concern (HPM-CC): The CONCERN Study

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Sheetal Sood

Senior Executive Compliance Officer, NYC Health + Hospitals

Talk Title: Automating Information Governance: Is AI The Key?

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Parsa Mirhaji MD, Ph.D.

Director, Center for Health Data Innovations at the Albert Einstein College of Medicine and Montefiore Medical Center

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

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Andy Merrill

VP of Payment Integrity R&D, Optum

Talk Title: Opening Keynote: Adopting AI Capabilities? Lessons From the Front Lines

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Madhuri Sebastian

VP AI Clinical Partnerships, GE Healthcare

Talk Title: AI in Healthcare Imaging - Opportunities and Challenges

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Rajeev Ronanki

SVP and Chief Digital Officer, Anthem

Panel Title: Population Health: A Data-Driven Model for Patient Care

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Jodie Gillon

Global Medical Lead, Patient Engagement Rare Disease, Pfizer

Panel Title: Leveraging AI For Diagnosis

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Vish Anantraman

Chief Innovation Architect, Northwell Health

Panel Title: Population Health: A Data-Driven Model For Patient Care

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Michael Recht

Chair of the Department of Radiology, NYU Langone

Talk Title: AI in Radiology: Threat or Opportunity?

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Emmanuel Fombu

Director, Digital Medicine and Innovation, Novartis

Talk Title: The Future of Healthcare: Humans and Machines Partnering for Better Outcomes

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Viraj Patwardhan

Vice President of Digital Design and Consumer Experience, Thomas Jefferson University Hospitals

Talk Title: Smart Patient Room Concierge

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Jesse Bridgewater

VP of Data Science, Livongo

Panel Title: Population Health: A Data-Driven Model For Patient Care

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Esteban Rubens

Global Principal for Enterprise Imaging, Pure Storage

Talk Title: Infrastructure Matters: Bringing Deep Learning to Enterprise Imaging Clinical Practice

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Susan Abedi

EVP Commercial Solutions, 81qd

Panel Title: Leveraging AI For Diagnosis

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Michael Frank

Director of Strategy Worldwide R&D, Pfizer

Talk Title: Machine Learning to Boost R&D Productivity in Pharma

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Christopher Lehmuth

Sr. Director of Enterprise Data Science, Express Scripts

Talk Title: Breaking the Cycle: Moving From Issue Management to Prevention with Predictive Analytics

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Len Usvyat, Ph.D.

Vice President of Integrated Care Analytics, Fresenius Medical Care

Talk Title: Applying Data Science to Understand and Improve Quality of Life in Patients with Chronic Disease

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Isabelle Lousada

Founder and CEO, ARC

Panel Title: Leveraging AI For Diagnosis

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Michelle Stansbury

VP of Corporate Business / Revenue Cycle Systems and Innovations, Houston Methodist

Talk Title: Creating A Digital Workforce: Implementing Intelligent Automation in Hospital Operations

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Christopher Steel

Senior Director of AI & Machine Learning, IQVIA

Talk Title: Building Business Value: Using AI and Machine Learning to Reduce Costs, Increase Revenue, and Drive Competitive Differentiation

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Vishaal Virani, M.D.

Client Success Director, ADA Health

Talk Title: How Chatbots Will Positively Transform Care for Patients

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Michael Berger

VP, Population Health Informatics & Data Science, Mount Sinai Health System

Talk Title: Decision-Centricity: Operationalizing Analytics and Data Science in Health Systems

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Sanji Fernando

VP Center for Applied Data Science, OptumLabs

Panel Title: Population Health: A Data-Driven Model for Patient Care

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Bülent Kiziltan Ph.D.

Former Head of Deep Learning, Aetna

Talk Title: Creating Value With AI

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Erik Pupo

Chief Information Officer, Columbia University Irving Medical Center

Panel Title: Population Health: A Data-Driven Model for Patient Care

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Adam Jenkins

Data Science Lead, Biogen

Talk Title: Real World Issues During Implementing AI In The Healthcare System

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Pamila Brar

Chief Medical Officer of the Health Nucleus and Senior Vice President, Human Longevity, Inc

Panel Title: Transforming Prevention through AI

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John Fahrenbach

Healthcare Data Scientist, UChicago Medicine

Talk Title: Augmenting Hospital Operations with AI

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Mark Kanner, Ph.D.

Lead Data Scientist, Aetna

Talk Title: How AI Can Help in Making Our Healthcare System More Efficient

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Tawnya Infantino

Senior Director of Digital Products, Dignity Health

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.

About

Artificial intelligence could be the last invention that humankind needs to make. As such, we think it’s pretty important we get it right. In 2019, Ai4 conferences will educate 1500+ top executives & data practitioners at the world’s largest companies about how they can responsibly leverage AI today. Confusion is still commonplace when discussing AI for the enterprise; from basic definitions all the way to implementation. Through our conferences and content, we aim to provide a common understanding for what AI means to the enterprise. Visit our homepage to learn about each of our conferences: Ai4 Finance, Ai4 Healthcare, Ai4 Cybersecurity, and Ai4 Retail.