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

The full agenda will be announced shortly. Previous speakers include:

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Ben Glocker

Lecturer, Medical Image Computing

Imperial College London

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Neil Lawrence

Professor of Machine Learning & Computational Biology

University of Sheffield

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Pearse Keane

NIHR Clinician Scientist

Moorfields Eye Hospital

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Brendan Frey

Co-Founder & CEO

Deep Genomics

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Polina Mamoshina

Research Scientist

Insilico Medicine

More Speakers Coming Soon

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Get to know the speakers

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Moorfields Eye Hospital in London is nearly nine months into a collaboration with the deep learning specialists DeepMind and is aiming to have a working algorithm in production that can make diagnoses from eye scans by the end of the year.

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"To understand deep learning in the context of genetic disease, you need to understand shallow learning first. Shallow learning relates mutations to diseases by looking for mutations that commonly occur in patients with a disease. It’s a commonly used method", Brendan Frey, Deep Genomics.

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Insilico Medicine launched aging.AI, a system allowing users to guess their age and gender by entering the results of their blood test. The system is focused on gamification of consumer blood testing and attracting the attention of the general public to the importance of periodic blood tests.

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Why Attend

Speakers

Healthcare 3.0

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.

Tech

Discover Emerging Trends & Best Practices

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

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.

Topics we cover

Machine Learning
Machine Learning
Personalised Medicine
Personalised Medicine
Clinical Patient Care
Clinical Patient Care
Pattern Recognition
Pattern Recognition
Image Retrieval
Image Retrieval
MedTech
MedTech
Data Security
Data Security
Ethics
Ethics

Previous attendees include

Accenture
Imperial
Bloomblisser
GSK
babylon health
philips
Toshiba Medical
Papworth Hospital
Google
nhs
astrazeneca
Samsung

Venue

Venue details to be announced.

View more information on hotels, restaurants, and things to do in London on our Pinterest page.

London

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For enquiries about the event or to pay via invoice please contact the summit creator Ka Lai Brightley-Hodges via kalai@re-work.co

Sponsored by

Previous sponsors include:

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Nvidia usa.001

Media Partners & Press

Previous partners include:

Doctorpreneurs.001
Iot do.001
Tractica.001
Startup health.001
The guardian.001
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Deeplearningweekly

As Featured In

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