Please use this identifier to cite or link to this item:
http://hdl.handle.net/11434/2233
Title: | Mechanised triage: A pilot study investigating the role of machine learning to triage penile lesions. |
Epworth Authors: | Murphy, Declan Lawrentschuk, Nathan |
Other Authors: | O'Brien, Jonathan Nandakishor, Kishor Chen, Kenneth Teh, Jiasian Kelly, Brian Manning, Todd Sathianathen, Niranjan Chee, Justin Palaniswami, Marimuthu |
Keywords: | Penile Squamous Cell Carcinoma PSCC Psychosocial Consequences Social Stigma Culturally Appropriate Care Machine Learning Smartphone Photography Artificial Intelligence Algorithm |
Issue Date: | Oct-2023 |
Conference Name: | Epworth HealthCare Research Month 2023 |
Conference Location: | Epworth Research Institute, Victoria, Australia |
Abstract: | Penile squamous cell carcinoma (PSCC) is a rare disease with devastating psychosocial consequences. Early recognition and treatment are paramount to preserving function and long-term survival. However, many men present with advanced disease due to a lack of awareness, social stigma, and limited access to culturally appropriate care. There is an urgent need to reduce barriers to subspecialist penile cancer care, especially for men from low socioeconomic backgrounds. Machine learning combined with smartphone photography has demonstrated growing utility by outperforming clinicians in diagnosing skin cancer. This project aims to evaluate the accuracy of an artificial intelligence algorithm for stratifying penile lesions. |
URI: | http://hdl.handle.net/11434/2233 |
Type: | Conference Poster |
Affiliated Organisations: | Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia Deartment of Urology, The Royal Melbourne Hospital, Melbourne, Victoria Australia Division of Cancer Surgery, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, Victoria, Australia |
Type of Clinical Study or Trial: | Pilot Study |
Appears in Collections: | Research Week |
Files in This Item:
File | Description | Size | Format | |
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AUA 2023 Poster_Jonathan OBrien.pdf | 1.04 MB | Adobe PDF | View/Open |
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