• Times in EDT

  • 10:00

    WELCOME & OPENING REMARKS

  • CHALLENGES & TRANSFORMATION

  • 10:05
    Kilian Koepsell

    From Idea to Research to Implementation: Making a Real Difference

    Kilian Koepsell - Co-Founder & CTO - Caption Health

    Down arrow blue

    From Idea to Research to Implementation: Making a Real Difference

    Kilian has spoken previously about Caption Health’s approach to address echocardiogram variability with AI. The company has since earned FDA breakthrough device designation and 510(k) clearance for its AI-guided ultrasound system, Caption AI, and announced its first customer, Northwestern Medicine. Not every company with an AI and healthcare idea can say the same. Kilian will illustrate what’s necessary to move beyond the theoretical and create useful technology for medical professionals, improving patient care. He will also discuss the medical settings that can benefit from A (and the challenges), and his take on how AI can democratize care.

    Caption Health CTO and Co-Founder Kilian Koepsell leads the company’s efforts to use the latest in artificial intelligence and deep learning to bring the diagnostic power of ultrasound to more healthcare providers, democratizing access to healthcare and improving patient outcomes.

    Prior to co-founding Caption Health, he worked on developing computer vision algorithms matched to the human visual processing system at the Redwood Neuroscience Institute and UC Berkeley — research he brought to Caption Health’s ultrasound guidance software. He also co-founded White Matter Technologies and was a founding team member at IQ Engines, which was acquired by Yahoo! for its Flickr group. He holds a PhD in physics from the University of Hamburg, as well as two master's degrees in mathematics and physics from the same university.

    Twitter Linkedin
  • AI IN HEALTHCARE: TOOLS & TECHNIQUES

  • 10:30
    Mathieu Galtier

    How to Put Patient Privacy First in Healthcare AI

    Mathieu Galtier - Chief Product Owner - Owkin

    Down arrow blue

    How to Put Patient Privacy First in Healthcare AI

    Mathieu is the Chief Product Officer at Owkin where he leads the design of Owkin product: a collaboration platform between medical researchers and data scientists powered by federated learning.

    Mathieu graduated from ENS and Mines ParisTech and completed his PhD in Machine Learning applied to Neuroscience at Oxford and Inria. He started his career at Dreem, a neurotech startup, where he directed research and algorithms and led the Morpheo project. He is devoted to deploying AI in a responsible way. He now leads Owkin’s Product team.

    Twitter Linkedin
  • 10:55
    Enrico Santus

    Making sense of Big Data - Challenges and Opportunities with NLP

    Enrico Santus - Senior Data Scientist - Bayer

    Down arrow blue

    Making sense of Big Data - Challenges and Opportunities with NLP

    The recent pandemic has shown that despite the incredible amount of available data, we are still unable to turn it into actionable insights. After discussing the current costs of not exploiting this information, I will describe a series of recent works where Natural Language Processing and, more in general, Artificial Intelligence techniques have been utilized to optimize clinical processes, drug development and adverse events monitoring.

    Enrico Santus is a senior data scientist at Bayer. After his PhD at the Hong Kong Polytechnic University, Enrico joined the group of Regina Barzilay at CSAIL, MIT. His academic career includes affiliations with the King's College of London, the University of Pisa, the University of Stuttgart, the Nara Institute of Technology and Harvard. His work touches topics such as NLP in Oncology, Cardiology and Palliative Care. Enrico has also worked on Epidemiology, Fake News Detection, Sentiment Analysis and Lexical Semantics. As of today, Enrico has published over 50 papers, with over 637 citations. He collaborated to the creation of The Prayer (artist: Diemut Strebe), a mouth-shaped robot that pronounces original prayers, generated with Artificial Intelligence, exposed at the Centre Pompidou, in Paris. He was also involved in the creation of Safe Paths, the MIT tracing app.

    Twitter Linkedin
  • 11:20

    COFFEE BREAK

  • HEALTHCARE SOLUTIONS

  • 11:35

    Sensemaking for Life Sciences in the Age of Big Data

  • David Shaprio

    Speaker:

    David Shaprio - VP of Product - H1

    Down arrow blue

    Sensemaking for Life Sciences in the Age of Big Data

    The sources of information necessary for healthcare and life sciences professionals to deliver value continue to expand and grow deeper. At the same time, the insights needed grow ever more precise. How will life sciences professionals find the information they need? One of the key challenges is identifying the right healthcare professional or key opinion leader for a given topic, therapeutic area or indication. Ultimately, healthcare is about connections between people, so how do we find the right people? Through the thoughtful application of AI tools in combination with human subject matter experts, we can unlock the hidden knowledge in big data and make the human connections that lead to innovation and improved health and patient outcomes.

    Dave Shapiro is the VP of Product at H1, a start-up focused on creating a healthier future by delivering a platform that connects stakeholders across the healthcare ecosystem. Dave has spent his career building software products as both an engineer and product manager. Dave graduated from the University of Pennsylvania with a degree in Computer Science. He has built enterprise applications to power financial institutions and architected search solutions for media companies. His focus on big data driven products started in fintech and market data and he honed his user experience focus at one of the leading food delivery platforms. Most recently Dave has led product at startups making an impact in healthcare through the use of data to drive better outcomes for stakeholders throughout the system.

    Twitter Linkedin
  • Julie Stern

    Speaker:

    Julie Stern - SVP Of Engineering - H1

    Down arrow blue

    Sensemaking for Life Sciences in the Age of Big Data

    The sources of information necessary for healthcare and life sciences professionals to deliver value continue to expand and grow deeper. At the same time, the insights needed grow ever more precise. How will life sciences professionals find the information they need? One of the key challenges is identifying the right healthcare professional or key opinion leader for a given topic, therapeutic area or indication. Ultimately, healthcare is about connections between people, so how do we find the right people? Through the thoughtful application of AI tools in combination with human subject matter experts, we can unlock the hidden knowledge in big data and make the human connections that lead to innovation and improved health and patient outcomes.

    Julie Stern is the SVP of Engineering at H1, a start-up focused on creating a healthier future by delivering a platform that connects stakeholders across the healthcare ecosystem. Julie graduated from Carnegie Mellon University with a degree in Mathematics and Computer Science. For the last 16 years, Julie has focused on leveraging the power of NLP and Machine Learning to make Healthcare data actionable. In products ranging from revenue cycle management, patient engagement, predicting health events, improving health outcomes, and applying guideline directed medical therapies, Julie has focused on leveraging the power of health data to improve lives.

    Twitter Linkedin
  • 12:00

    Delivering A Higher Value Care

  • 12:25
    Christophe Aubry

    Hybrid AI Approach to Knowledge Discovery

    Christophe Aubry - Head of Sector Strategy, Healthcare - Expert.AI

    Down arrow blue

    Hybrid AI Approach to Knowledge Discovery

    Global biomedical content represents critical data for healthcare organizations, which cannot be easily handled by business applications because it is unstructured and varies across different data sources. With speed and accuracy necessities in the medical field, organizations must find a way to overcome this barrier to understanding language. A hybrid approach to AI, combining the strengths of both natural language understanding and machine learning, provides an ideal solution that mimics the human-like comprehension of biomedical content such as clinical trials, real-world data, medical reports, literature, and social media. This capability can help to accelerate drug discovery and development, innovate faster and increase access to healthcare.

    Key Takeaways:

    • How Hybrid AI can accurately transform clinical trials data, real world data and scientific literature into knowledge and insight.

    • How Hybrid AI can overcome the need of exhaustive training data sets required for pure machine learning based approach

    • How Hybrid AI can be explainable by design and overcome the black box phenomenon associated with machine learning

    Christophe Aubry leads business activities in specialized markets for expert.ai, the leading provider of AI-based Natural Language Understanding solutions. As a strategic technology leader focused on delivering solutions that solve customer pain points, Christophe has dedicated the last 20 years of his career to creating business value for clients worldwide. He helped his company establish its presence in North America, earning and consolidating the trust of major clients in Media, Publishing, Life Sciences, or Government sectors. Christophe started his career as a Product Manager at IBM in the early stages of data and text mining. As a co-founder and Vice President Professional Services at TEMIS for more than 10 years, he molded talents to help them reach their highest potential while supervising customer deployments in all geographies and leading strategic service activities. His favorite quote is “A company’s employees are its greatest assets and your people are your product”. Christophe has a deep understanding and passion for A.I. technologies. He holds a Master’s Degree in Applied Mathematics and Computer Sciences.

    Twitter Linkedin
  • 12:50

    ROUNDTABLE DISCUSSIONS

  • Camille Marini

    ROUNDTABLE: Accelerating Drug Discovery by Competitive Cooperation Through Open Source

    Camille Marini - CTO - Owkin

    Down arrow blue

    Roundtable: Accelerating Drug Discovery by Competitive Cooperation Through Open Source

    MELLODDY is a pharma consortium on drug discovery. It aims to leverage the world’s largest collection of small molecules with known biochemical or cellular activity to enable more accurate predictive models and increase efficiencies in drug discovery. Pharma partners include: Amgen, Astellas, AstraZeneca, Bayer, Boehringer Ingelheim, GSK, Janssen, Merck, Novartis and Servier.

    As Chief Technology Officer of Owkin, Camille currently leads the development of a collaborative machine learning platform designed for data scientists and medical experts. Prior to joining Owkin, Camille was an academic researcher and worked in startups focused on reproducible and traceable AI. She graduated from Mines ParisTech and completed her Ph.D. in applied data science at the Université Pierre et Marie Curie.

    Twitter Linkedin
  • Christophe Aubry

    ROUNDTABLE: Hybrid AI and Beyond: Demo & Discussion

    Christophe Aubry - Head of Sector Strategy, Healthcare - Expert.AI

    Down arrow blue

    Hybrid AI Approach to Knowledge Discovery

    Global biomedical content represents critical data for healthcare organizations, which cannot be easily handled by business applications because it is unstructured and varies across different data sources. With speed and accuracy necessities in the medical field, organizations must find a way to overcome this barrier to understanding language. A hybrid approach to AI, combining the strengths of both natural language understanding and machine learning, provides an ideal solution that mimics the human-like comprehension of biomedical content such as clinical trials, real-world data, medical reports, literature, and social media. This capability can help to accelerate drug discovery and development, innovate faster and increase access to healthcare.

    Key Takeaways:

    • How Hybrid AI can accurately transform clinical trials data, real world data and scientific literature into knowledge and insight.

    • How Hybrid AI can overcome the need of exhaustive training data sets required for pure machine learning based approach

    • How Hybrid AI can be explainable by design and overcome the black box phenomenon associated with machine learning

    Christophe Aubry leads business activities in specialized markets for expert.ai, the leading provider of AI-based Natural Language Understanding solutions. As a strategic technology leader focused on delivering solutions that solve customer pain points, Christophe has dedicated the last 20 years of his career to creating business value for clients worldwide. He helped his company establish its presence in North America, earning and consolidating the trust of major clients in Media, Publishing, Life Sciences, or Government sectors. Christophe started his career as a Product Manager at IBM in the early stages of data and text mining. As a co-founder and Vice President Professional Services at TEMIS for more than 10 years, he molded talents to help them reach their highest potential while supervising customer deployments in all geographies and leading strategic service activities. His favorite quote is “A company’s employees are its greatest assets and your people are your product”. Christophe has a deep understanding and passion for A.I. technologies. He holds a Master’s Degree in Applied Mathematics and Computer Sciences.

    Twitter Linkedin
  • 13:15

    COFFEE BREAK

  • STARTUP SESSION

  • 13:30

    The Power of Genome Editing

  • 13:55

    PANEL: Harness the Full Value of Your Data

  • 14:30

    1:1 Speed Networking

  • 15:00

    END OF SUMMIT

This website uses cookies to ensure you get the best experience. Learn more