It’s a game-changer in medicine.
A new artificial intelligence tool called PanDerm may significantly enhance the speed and accuracy of diagnosing melanoma and other skin conditions, according to a recent study published in Nature Medicine.
Developed by an international team of researchers, PanDerm boosted physicians’ accuracy in identifying skin cancer by 11% and improved the diagnosis of a wide range of other dermatological conditions by nearly 17%, the study found.
Designed to support medical professionals, PanDerm helps interpret complex skin images, making it easier for clinicians to reach confident decisions, said senior author Zongyuan Ge, associate professor of data science and AI at Monash University in Australia.
Given that around 70% of people experience some form of skin disorder, early and accurate detection is essential for effective treatment, researchers noted.
PanDerm was trained on over 2 million skin-related images, covering four types of medical imaging. Unlike previous AI models, which struggled to integrate varied imaging formats, PanDerm was built to analyze a diverse range—from microscopic slides to wide-field photos of skin lesions.
Earlier models often underperformed in clinical settings due to their inability to process different image types. “PanDerm overcomes that by mimicking how dermatologists synthesize visual data from multiple sources,” said lead researcher Siyuan Yan, a PhD student at Monash University’s Faculty of Engineering.
During the study, the AI system was evaluated on numerous tasks, including skin cancer screening, tracking changes in moles, counting lesions, and diagnosing other skin conditions. PanDerm consistently delivered accurate results, often needing only 5% to 10% of the data typically required for these diagnoses.
Peter Soyer, director of the Dermatology Research Center at the University of Queensland, noted that such technology could be especially valuable in underserved regions where access to dermatologists is limited.
Although promising, researchers stressed that further testing is needed to validate PanDerm’s effectiveness across different clinical environments and patient populations before it can be widely implemented.
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