at the University of Melbourne
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Gain insights and tips to help your family manage better through lockdown.
Covid-19 has forced many families to adapt to a new reality of remote learning, working from home, cancellation of social activities and more time spent with family members which can raise the emotional temperature for everyone.
There is no doubt lockdowns are a stressful time for families, however there are also many things we can do to support and improve our wellbeing during these times.
During this discussion, our panel of health and wellbeing experts along with community members,will provide insights and tips on how families can work together to manage through lockdowns including the role parents can play, maintaining hope, tips to improve motivation for young people and more.
The webinar is ideal for families with children across Australia and allied health professionals who provide services for families. Audience questions are welcome on the day following the discussion.
The webinar is hosted by Professor Jane Gunn, Dean, Faculty of Medicine, Dentistry and Health Sciences at the University of Melbourne, and forms part of the ‘In pursuit of health’ event series.
Though the potential of artificial intelligence (AI) in healthcare warrants genuine enthusiasm, meaningful impact will require careful integration into clinical care. AI tools are susceptible to mistakes and rarely capable of capturing all of the nuances pertaining to a complex clinical situation. Thus, we propose approaches designed to augment, rather than replace, clinicians during clinical decision making.
In this talk, Associate Professor Jenna Wiens will highlight three related research directions pertaining to:
i) a transfer learning approach for mitigating potentially harmful shortcuts when making diagnoses
ii) a simple yet accurate deterioration index that generalizes across hospitals and
iii) lessons learned during deployment of a risk stratification tool for predicting healthcare-associated infections.
In summary, there’s a critical need for machine learning in healthcare; however, the safe and meaningful adoption of these techniques will require collaboration between clinicians and AI.