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AI & Machine Learning in Healthcare

Demystifying AI, Machine Learning and Robotics in Healthcare

16-17 November 2021 | Rendezvous Hotel

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Early Bird Rate (Save $400) Expires on 8 October 2021 // See Pricing Below

overview

The AI & Machine Learning in Healthcare Conference will be returning for its 3rd year. This event has been designed to cater to a unique mix of stakeholders and will be attended by heads of innovation, clinicians, digital health and transformation managers, health informaticians, healthcare IT professionals.

The agenda will focus in on real insights on implementation and experiences in different and niche clinical settings. Radiology, Oncology, Pathology and hospital, surgery will be highlight how AI & Machine Learning can not only improve efficiencies but improve health outcomes for the patient and the medical practitioner.

Furthermore, the event will explore how clinicians and industry alike can leverage these emerging technologies to unlock opportunities for discovery and detection, enable greater accuracy, and provide the consumer with greater choice.

Governance, data, privacy, and legality issues will form the underlying theme of the conference. The event will ask the fundamental questions: who is responsible when AI does something? How is governance supporting innovation in healthcare? How do you find & address solutions to funding in the commercial space?

Finally, what will be next for AI & Machine Learning in healthcare? Have we finally moved away from ultimate knowledge and accepting AI & ML as decision assistance?

TOPICS TO BE ADDRESSED INCLUDE:

  • Harnessing data to its full potential to enable the clinical application of AI in Canada
  • The implementation of Radiology based AI in a clinical setting
  • AI and Radiomics – The Future of Medical Imaging in Oncology
  • Bringing AI into clinical practice within the pathology space
  • Creating an AI Ecosystem at Metro South Hospital and Health Service
  • How can clinicians and industry leverage these emerging technologies to drive efficiencies?
  • Digital surgery 4.0 the next revolution: using AI & Robotics to drive efficiencies
  • Machine learning in bio-medical image analysis
  • Medical Device regulations: the ethical and regulatory framework in Australia
  • How are hospitals investing in innovation?
  • Privacy and data protection implications for AI in healthcare
  • Permission based remote patient monitoring for detection and treatment
  • The use of AI in high throughput Covid-19 drug screening and vaccine design
  • Using AI for Clinical Trial Design
  • How can the application of natural language processing and predictive modelling offer us in terms of better trial design & better ROI?
  • Unlocking opportunities for discovery and detection in healthcare: hesitations & barriers for clinicians
  • The Rise of the Healthcare Consumer – Driving a Better Experience for Patients
  • What do cloud technologies add to genomics and Australian Healthcare?
  • From Commercialisation to building a Hub to AI: what you need to know
  • Navigating the funding path – finding & addressing solutions in the commercial space
  • How do we ensure & enable greater accuracy?

speakers

Dr Nikolai Petrovsky

Professor, College of Medicine & Public Health, Flinders University, Chairman & Research Director, Vaxine

Dr Louise Sun

Cardiac Anaesthesiologist, AI Epidemiologist and Director of Big Data and Health Bioinformatics Research, University of Ottawa Heart Institute

Dr Terry Sweeney CMG

Chief Executive Officer, Digital Health Cooperative Research Centre

Ella Cannon

Associate Principal, Hive Legal

Professor Ian Scott

Director of Internal Medicine and Clinical Epidemiology, Princess Alexandra Hospital

Chris Kaias

Senior Associate, Hive Legal

Dr Carolyn Johnston

Research Fellow, University of Tasmania, Senior lecturer (honorary appointment) Melbourne Law School, Clinical Ethicist, Monash Children’s Hospital Melbourne

A/Prof Chris Hensman

General and Robotic Surgeon, Conjoint Lecturer, Monash University, University of Adelaide

Dr Stefan Harrer

Chief Innovation Officer, Digital Health CRC

Associate Professor Tam C. Nguyen

Deputy Director of Research, St Vincent's Hospital Melbourne

Michelle Gallaher

Chief Executive Officer, Opyl

Scott Thomson

Head of Innovation, Customer Engineering, Google

Bronwyn Le Grice

Founder, CEO & Managing Director, ANDHealth

Dr Greg Bass

Senior Scientist, CSL

Dr Michelle Perugini

Co-Founder and CEO, Presagen and Life Whisperer

Dr Hyun Soo Ko

Consultant Radiologist, MD, FRANZCR, Peter MacCallum Cancer Centre, Melbourne Epworth Medical Imaging, Epworth Freemasons Hospital, East Melbourne, Honorary Clinical Lecturer, University of Melbourne

Brent Barnes

CEO and Managing Director, LBT Innovations

Dr Ingmar Wahlqvist

Senior Investment Manager, Brandon Capital Partners

A/Prof Shlomo Berkovsky

Australian Institute of Health Innovation, Macquarie University

Dr Natalie Twine

Research Scientist and Genome Insights Team Lead, CSIRO

Dr Lee Walsh

Founder & Regulatory Principal, Platypus Technical, former Technical Lead (Digital Health), Therapeutic Goods Administration (TGA)

Deepak Biswal

Founder & CEO, CareMonitor

Dr Johan Verjans

Deputy Director, Medical Machine Learning, Australian Institute of Machine Learning

Dr James Hughes

Lecturer and Researcher in the School of Nursing, QUT

Dr Paul Lane

Medical Director, Townsville University Hospital

Dr Rob Grenfell

Health Director, Health & Biosecurity, CSIRO

Dr Dean Ho

Head, Department of Biomedical Engineering, Director, The N.1 Institute for Health (N.1), Provost’s Chair Professor (Director, The Institute for Digital Medicine (WisDM)), National University of Singapore

Jason Chuen

Director, 3d Med Lab, Director, Department of Vascular Surgery, Austin Health

agenda

9:00 am

OPENING | Opening remarks from the Chair

Dr Rob Grenfell, Health Director, Health & Biosecurity, CSIRO

9:10 am

Dr Louise Sun is a data expert, as well as a clinical data scientist, cardiologist, and epidemiologist. To Louise, the clinical application of AI & Machine Learning in healthcare, all start with data, big data. But what is the implementation of these? What can you use this data for? Can you train different tools with this data? Dr Sun will provide rapid key examples and studies and how AI can be used in multiple settings such as medical imaging & rural & remote. Finally, Dr Louise Sun will address how to implement AI and champion AI locally? How can you get your colleagues & administrators onboard?

THE IMPLEMENTATION & LEARNINGS OF AI & MACHINE LEARNING IN A CLINICAL SETTING

9:45 am

  • Overcoming barriers and hesitations
  • Decision assistance and improving efficiencies
  • Legality and governance

10:15 am

CASE STUDY | AI and Radiomics - The Future of Medical Imaging in Oncology

Dr Hyun Soo Ko, Consultant Radiologist, MD, FRANZCR, Peter MacCallum Cancer Centre, Melbourne Epworth Medical Imaging, Epworth Freemasons Hospital, East Melbourne, Honorary Clinical Lecturer, University of Melbourne

10:45 am

Networking break

11:15 am

  • The nitty gritty of bringing your AI into reality
  • Challenges entering the global market
  • Leading the way in Microbiology AI – The first and only FDA cleared culture plate reader
  • Overcoming customer objections – Proving the technology works
  • Building awareness and engaging stakeholders
  • Working alongside St Vincent’s, Melbourne

11:45 am

  • Developing and validating AI & Machine Learning applications in hospital practice
  • Engaging stakeholders
  • Developing governance structure
  • Ensuring applications are fit for purpose, fair and free of bias, their outputs and effects on patient care evaluated
  • Ethical and legal issues regarding data privacy and liability for application error

1:00 pm

Lunch & networking break

2:00 pm

  • The tools to aid safer and better surgery
  • Heightening consumer-based healthcare
  • Improving efficiencies
  • Improving surgeon’s performance

2:30 pm

Machine learning in bio-medical image analysis

Dr Greg Bass, Senior Scientist, CSL

GOVERNANCE, REGULATIONS & PRIVACY & DATA

3:00 pm

  • What sort of AI & Machine Learning does the regulation define as a medical device?
  • What are the challenges faced for innovators within the clinical setting?
  • Helping businesses navigate & understand regulations for successful technologies

3:30 pm

Networking break

4:00 pm

  • What other innovations like AI & ML are hospitals looking to invest in?
  • Virtual hospitals and the future of Virtual Hospitals in a post-COVID world
  • Gaining top-down approval & engaging stakeholders
  • Addressing the barriers in overcoming investment
  • What does the future look like for AI & ML in healthcare?

4:30 pm

This session will look at some of the broader privacy and data protection issues that are associated with AI & machine learning in the healthcare setting. Ella & Chris from Hive Legal will draw on their specialisations and explore the use of de-identified patient data and the risk of re-identification, the issue of informed patient consent, and some key data protection and cybersecurity risks.

5:00 pm

This session will explore how using world data and making it useable and accessible will improve patient outcomes. This solution-based session will delve into cloud technologies, remote patient monitoring, real-time scheduling that will all help and assist the continuity of care from home. What will be next for Google? What may happen in the future with AI & ML in Healthcare?

5:35 pm

CLOSING | Closing remarks from the Chair

5:40 pm

Networking Drinks

9:00 am

OPENING | Opening remarks from the Chair

Associate Professor Tam C. Nguyen, Deputy Director of Research, St Vincent's Hospital Melbourne

USING AI FOR CLINICAL TRIALS & VACCINE DEVELOPMENT

9:10 am

OPENING ADDRESS | The use of AI in high throughput Covid-19 drug screening and vaccine design

Dr Nikolai Petrovsky, Professor, College of Medicine & Public Health, Flinders University, Chairman & Research Director, Vaxine

9:40 am

We know that AI technologies have advanced to a level of maturity that allows them to be employed under real-life conditions to assist human decision-makers. It has the potential to transform key steps of clinical trial design from study preparation to execution towards improving trial success rates, thus lowering the pharma R&D burden and speeding up the drug development cycle. This session will discuss issues around scalability and interoperability, and patient privacy as well as ethical aspects of AI models.

9:55 am

  • What’s the commercialisation potential of this work?
  • What are the challenges around data integrity?
  • How competitive is this space?
  • What is the most significant technical hurdles in applying AI?
  • How disruptive will this technology be in the clinical trials market?
  • What are the measurable improvement impacts and use-case likely to be?

EMERGING TECHNOLOGIES IN CONSUMER BASED HEALTHCARE

10:25 am

  • How might clinicians draw value from AI & ML?
  • What AI & ML technologies are proving most useful?
  • What are the limitations/barriers of getting this technology into use in a clinical setting?
  • Barriers to adoption and are clinicians adopting them?
  • Where are the best opportunities for AI & ML innovations? How could this impact current health practices?

11:05 am

Networking break

11:35 am

Patient experience and patient reported outcomes are playing a bigger part of Australian healthcare. As we move from activity-based funding to value based care, the voice of the patient as a consumer is increasingly important. As we start to expect the same level of service as we do from shopping online, booking a hotel or ordering a ride share, what lessons can we learn from other countries?  How can technology drive a better experience and give the consumer more choice? This session will explore how we can use data and technology to drive an improved experience and allow consumers to make a more informed choice about their healthcare services.

12:10 pm

With a move to the cloud inevitable. The fast moving, hard to compare and potentially mutually exclusive field, can be very confusing. CSIRO’s Transformational Bioinformatics group are using a multitude of cloud providers and machine learning approaches to build an array of revolutionary and scalable data analysis platforms. This session will explore what do cloud based technologies add to Australian healthcare with a focus on genomics platforms.

12:40 pm

  • Using AI & Machine Learning across different medical fields
  • How do you set up this? What are the barriers & hesitations?
  • What are the important aspects to connect to?
  • Data & commercialisation

1:10 pm

Lunch & networking break

2:10 pm

James’s background combines clinical and research, focusing on interventions to improve pain care in the emergency department. In conjunction with the Australian eHealth Research Centre (CSIRO) he has developed machine and deep learning techniques to identify patients presenting in pain to the emergency department based on their initial assessment.

2:45 pm

  • Path to commercialisation – creating a solution to a redundant problem?
  • Joining up the ecosystem & innovations with clinicians with buyers
  • Navigating that path and making it easier for future funding
  • Accessing the right decision makers

3:30 pm

  • Human engagement with AI for interventional healthcare
  • Acquiring data the right way & what is quality data
  • Using individual data to treat the individual rather than population data. How does this increase accuracy?
  • Can AI help us discover drug-drug interactions & drug dose amounts?

4:05 pm

CLOSING | Closing remarks from the Chair

4:10 pm

Conference Closed

Partners

pricing

Packages Price
Virtual Pass$1295$1095+GST Early Bird Rate Early Bird Rate
Premium Pass$2495$2195+GST Early Bird Rate Early Bird Rate
Group Premium Pass (Up to 6 people)$7500+GST
Packages Price
Premium Pass$1795$1395+GST Early Bird Rate Early Bird Rate
Group Premium Pass (Up to 6 people)$7500+GST

Early Bird Rate – Expires on 8 October 2021

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Informa Health & Safety Commitments

When you join our event, you can expect to see that health and safety is a priority, and that a range of measures are in place to ensure everyone involved is able to enjoy a safe, hygienic, productive and high-quality organised event experience.

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To ensure the maximum safety of our audiences, Informa requires all in-person participants (speakers, delegates, partners, sponsors, exhibitors, suppliers) to be fully vaccinated in order to gain access to the physical event. For those unvaccinated or partially vaccinated, we encourage you to participate in the event by booking a virtual pass to attend the event.

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Event Health & Safety measures in place

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For more details please visit www.informa.com.au/healthsafety

when & where

16 - 17 Nov 2021

Rendezvous Hotel, Melbourne
328 Flinders Street
Melbourne VIC 3000

contact

Still have a question?

Katrina Bowns
Conference Producer
Katrina.Bowns@informa.com.au
02 9080 4026

Danielle Newman
Senior Business Development Manager
+61 2 9080 4318
Danielle.Newman@informa.com
02 9080 4432

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