Advance your skills and discover the impact of machine learning on healthcare in a half day training workshop with case studies and key insights

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Speakers

Confirmed speakers include:

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Nophar Geifman

Lecturer

University of Manchester

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David Clifton

Associate Professor of Engineering Science

University of Oxford

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Andreas Theodorou

Teaching Fellow

University of Bath

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Maria Chatzou

CEO

Lifebit

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New for 2020

  1. Deep Dive sessions to facilitate interactive discussions, practical workshops, & technical labs
  2. Event App to meet fellow attendees and personalize your schedule
  3. Multiple tracks to encourage cross-industry learnings & collaboration
  4. In-depth interviews with speakers available to watch again online
  5. Facilitated networking opportunities to make new connections
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An Introduction to Machine Learning in Healthcare

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Topics we cover

Machine Learning

Personalised Medicine

Clinical Patient Care

Pattern Recognition

Image Retrieval

MedTech

Data Security

Ethics

Machine Learning

Personalised Medicine

Clinical Patient Care

Pattern Recognition

Image Retrieval

MedTech

Data Security

Ethics

Why Attend

Our events bring together the latest technology advancements as well as practical examples to apply AI to solve challenges in business and society. Our unique mix of academia and industry enables you to meet with AI pioneers at the forefront of research, as well as exploring real-world case studies to discover the business value of AI.

  • Speakers

    Healthcare 3.0

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    AI & machine learning techniques are helping to shift from reactive to proactive and predictive care. How can we use increased computer processing power and personalised healthcare to improve patient outcomes, and apply AI and deep learning to make real-time predictions and actionable interventions.

  • Discover

    Discover Emerging Trends & Best Practices

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    How can we apply intelligent algorithms to rich data sets to transform medicine & ensure more accessible & efficient healthcare? How can ML be applied for triggering clinical pathways, patient risk stratification & predicting outcomes? What are the ethical, fairness & accountability issues?

  • Network

    Key takeaways

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    Explore machine learning frameworks, time-series analysis, deep learning and transfer learning methods. Learn the purpose of machine learning and the interpretation of predictive modeling results. Discover the digital future of healthcare and medicine and the key challenges to be considered.

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    Who Should Attend

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    • Data Scientists
    • Data Engineers
    • Healthcare Professionals
    • Founders
    • Investors
    • CTOs
    • Director of Engineering
  • Join

    Join the discussion

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    • 60 speakers
    • 550+ leading technologists & innovators
    • Group brainstorming sessions
    • Interactive workshops
    • 7 + hours of networking
    • Access to all the filmed presentations
    • Discover technology shaping the future
  • Download

    Downloads

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    View the summit brochure and all the information you need to convince your boss that attending the summit will help future-proof your business.

Confirmed attendees include

Imperial
VIAS Institute
PARI
WellVine
Federal Hearings and Appeals Services
Bournemouth University
Uni of Camb
Kings college london
Tunstall Nordic AB

Summary

Jeff Clune, Team Lead at OpenAI

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Presentation

Dawn Song, Professor of Computer Science at UC Berkeley

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Interview

Shalini Ghosh, Director of AI Research at Samsung Research

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Media Partners & Press

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As Featured In

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An Introduction to Machine Learning in Healthcare

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