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Integrating AI in melanoma care

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Manage episode 482649249 series 2943492
Content provided by Melanoma Institute Australia. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Melanoma Institute Australia 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://ppacc.player.fm/legal.

In this episode of Melanoma Insights for Professionals, we explore the cutting-edge role of artificial intelligence (AI) in diagnosing melanoma.

Join Dermatologists Prof Pascale Guitera and Prof Victoria Mar and Pathologist Dr Nigel Mayer as they unpack how AI is transforming clinical practice—from lesion detection and triage to deep learning in pathology and improving clinical education.

Discover the promise, limitations and ethical considerations of integrating AI into dermatology and pathology, and hear what's next on the horizon for both clinicians and patients.

This podcast is suitable for multidisciplinary specialists, primary care physicians, researchers and other healthcare professionals.

SPEAKERS

  • Prof Pascale Guitera - Dermatologist and Education Committee Chair, Melanoma Institute Australia | Director, Sydney Melanoma Diagnostic Centre at Royal Prince Alfred Hospital
  • Prof Victoria Mar - Director, Victorian Melanoma Service at The Alfred | Professor of DermatoOncology, the School of Public Health and Preventive Medicine, Monash University
  • Dr Nigel Maher - Pathologist, Melanoma Institute Australia | Chair of the AI Working Group, Royal College of Pathologists of Australasia

Please note that this podcast was accurate at the time of recording (May 2025) but may not reflect the rapidly evolving treatment landscape and approvals in Australia.

MIA’s Education Program is proudly supported through unrestricted educational grants from BMS, MSD and HEINE.

For more practice-changing clinical education, visit the Melanoma Education Portal.

  continue reading

27 episodes

Artwork
iconShare
 
Manage episode 482649249 series 2943492
Content provided by Melanoma Institute Australia. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Melanoma Institute Australia 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://ppacc.player.fm/legal.

In this episode of Melanoma Insights for Professionals, we explore the cutting-edge role of artificial intelligence (AI) in diagnosing melanoma.

Join Dermatologists Prof Pascale Guitera and Prof Victoria Mar and Pathologist Dr Nigel Mayer as they unpack how AI is transforming clinical practice—from lesion detection and triage to deep learning in pathology and improving clinical education.

Discover the promise, limitations and ethical considerations of integrating AI into dermatology and pathology, and hear what's next on the horizon for both clinicians and patients.

This podcast is suitable for multidisciplinary specialists, primary care physicians, researchers and other healthcare professionals.

SPEAKERS

  • Prof Pascale Guitera - Dermatologist and Education Committee Chair, Melanoma Institute Australia | Director, Sydney Melanoma Diagnostic Centre at Royal Prince Alfred Hospital
  • Prof Victoria Mar - Director, Victorian Melanoma Service at The Alfred | Professor of DermatoOncology, the School of Public Health and Preventive Medicine, Monash University
  • Dr Nigel Maher - Pathologist, Melanoma Institute Australia | Chair of the AI Working Group, Royal College of Pathologists of Australasia

Please note that this podcast was accurate at the time of recording (May 2025) but may not reflect the rapidly evolving treatment landscape and approvals in Australia.

MIA’s Education Program is proudly supported through unrestricted educational grants from BMS, MSD and HEINE.

For more practice-changing clinical education, visit the Melanoma Education Portal.

  continue reading

27 episodes

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