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AI, Quality and Big Data

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Manage episode 506754517 series 3668668
Content provided by Royal College of Pathologists of Australasia (RCPA). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Royal College of Pathologists of Australasia (RCPA) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode of The Pathology Report, host Dr Mags Strauss is joined by guests A/Prof Octavia Peck Palmer, Prof Leslie Burnett AM and Dr Timothy Fazio to explore the intersection of artificial intelligence, big data and pathology.

A/Prof Peck Palmer, a clinical chemist and director at the University of Pittsburgh Medical Center, discusses the importance of ensuring that big data reflects diverse populations and addresses healthcare equity, emphasising the need for collaboration between data experts and clinicians to address healthcare gaps effectively.

Prof Burnett AM, a pathologist from the Garvan Institute of Medical Research in Sydney and Virtus Diagnostics, sheds light on harnessing AI to augment human abilities in diagnostics without fear of overdiagnosis. He elaborates on how AI enables pathologists to manage larger datasets and uncover patterns that enhance diagnostic accuracy.

Dr Fazio, a health informatician and metabolic physician, delves into the practical applications of predictive modelling in clinical settings. He discusses the balance between AI handling simple tasks and the implications for clinician workload and education as AI takes on more complex responsibilities.

Key topics covered in the episode include:

  • The role of AI in enhancing pathology diagnostics and identifying healthcare disparities.
  • The impact of AI on overdiagnosis and how models mirror traditional diagnostic test characteristics.
  • Data ownership and sovereignty concerns, particularly relating to cross-border data sharing and ensuring patient consent.
  • Different views on implementing data insights in clinical and laboratory settings to personalise patient care.

They then reflect on the balance between routine automation and the potential cognitive burden on clinicians, emphasising the importance of evolving medical education to align with technological advancements.

RCPA Members

This podcast is an RCPA-endorsed CPD activity. Each episode gives you an opportunity to gain CPD hours in three easy steps:

  • Step 1. Listen or watch the podcast here, on your favourite podcast channel or on YouTube
  • Step 2. To claim your CPD hours, please complete and pass this short online quiz
  • Step 3. Sit back and let us load your CPD hours into your CPD profile for you

The Pathology Report is produced by the Royal College of Pathologists of Australasia and is part of the Talking HealthTech Podcast Network.


Learn more about the RCPA at rcpa.edu.au and discover other shows in the network at talkinghealthtech.com/podcast/network.

  continue reading

7 episodes

Artwork
iconShare
 
Manage episode 506754517 series 3668668
Content provided by Royal College of Pathologists of Australasia (RCPA). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Royal College of Pathologists of Australasia (RCPA) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

In this episode of The Pathology Report, host Dr Mags Strauss is joined by guests A/Prof Octavia Peck Palmer, Prof Leslie Burnett AM and Dr Timothy Fazio to explore the intersection of artificial intelligence, big data and pathology.

A/Prof Peck Palmer, a clinical chemist and director at the University of Pittsburgh Medical Center, discusses the importance of ensuring that big data reflects diverse populations and addresses healthcare equity, emphasising the need for collaboration between data experts and clinicians to address healthcare gaps effectively.

Prof Burnett AM, a pathologist from the Garvan Institute of Medical Research in Sydney and Virtus Diagnostics, sheds light on harnessing AI to augment human abilities in diagnostics without fear of overdiagnosis. He elaborates on how AI enables pathologists to manage larger datasets and uncover patterns that enhance diagnostic accuracy.

Dr Fazio, a health informatician and metabolic physician, delves into the practical applications of predictive modelling in clinical settings. He discusses the balance between AI handling simple tasks and the implications for clinician workload and education as AI takes on more complex responsibilities.

Key topics covered in the episode include:

  • The role of AI in enhancing pathology diagnostics and identifying healthcare disparities.
  • The impact of AI on overdiagnosis and how models mirror traditional diagnostic test characteristics.
  • Data ownership and sovereignty concerns, particularly relating to cross-border data sharing and ensuring patient consent.
  • Different views on implementing data insights in clinical and laboratory settings to personalise patient care.

They then reflect on the balance between routine automation and the potential cognitive burden on clinicians, emphasising the importance of evolving medical education to align with technological advancements.

RCPA Members

This podcast is an RCPA-endorsed CPD activity. Each episode gives you an opportunity to gain CPD hours in three easy steps:

  • Step 1. Listen or watch the podcast here, on your favourite podcast channel or on YouTube
  • Step 2. To claim your CPD hours, please complete and pass this short online quiz
  • Step 3. Sit back and let us load your CPD hours into your CPD profile for you

The Pathology Report is produced by the Royal College of Pathologists of Australasia and is part of the Talking HealthTech Podcast Network.


Learn more about the RCPA at rcpa.edu.au and discover other shows in the network at talkinghealthtech.com/podcast/network.

  continue reading

7 episodes

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