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Melanoma imaging and diagnosis: What does the future hold?
Lena von Schuckmann1, Leith Banney2, H Peter Soyer3
1BSc, MBBS, MPH, PhD, FRACGP, FACD, Senior Clinical Lecturer, Frazer Institute, The University of Queensland, Dermatology Research Centre, Brisbane, Qld; Senior Medical Officer, Dermatology Department, Princess Alexandra Hospital, Brisbane, Qld; Senior Medical Officer, Dermatology Department, Sunshine Coast University Hospital, Sunshine Coast, Qld; Private Practice, Spring Hill, Brisbane and Samford Valley, Moreton Bay, Qld.
Artificial intelligence (AI) aids melanoma diagnosis in Australia by improving early detection. Digital monitoring of moles may reduce unnecessary biopsies for high-risk patients.
Area of Science:
- Dermatology
- Medical Imaging
- Artificial Intelligence
Background:
- Early melanoma diagnosis is critical for patient survival.
- Artificial intelligence (AI) is increasingly adopted for melanoma diagnosis in Australia.
- Digital monitoring of naevi, particularly dysplastic naevi, can help manage patients at risk of melanoma.
Purpose of the Study:
- To discuss advancements in medical imaging for early melanoma diagnosis.
- To highlight the role of AI in improving diagnostic accuracy.
- To explore strategies for reducing unnecessary biopsies in melanoma management.
Main Methods:
- Review of current literature on AI in melanoma diagnosis.
- Discussion of digital monitoring techniques for naevi.
- Analysis of whole-body imaging for lesion detection.
Main Results:
- AI offers potential for more accurate and earlier melanoma detection.
- Digital monitoring can assist in identifying changing lesions, potentially reducing biopsies.
- Whole-body imaging aids in focusing clinical attention on significant changes.
Conclusions:
- AI and advanced imaging techniques are transforming melanoma diagnosis.
- Optimizing diagnostic pathways can improve patient outcomes and reduce healthcare burdens.
- Balancing biopsy benefits against potential harm is essential in melanoma management.
