Publications by authors named "P Gottfrois"
Psoriasis, a chronic inflammatory skin disease, affects millions of people worldwide. It imposes a significant burden on patients' quality of life and healthcare systems, creating an urgent need for optimized diagnosis, treatment, and management. In recent years, image-based artificial intelligence (AI) applications have emerged as promising tools to assist physicians by offering improved accuracy and efficiency.
View Article and Find Full Text PDFAI-powered visual diagnosis of vulvar lichen sclerosus: A pilot study.
J Eur Acad Dermatol Venereol
December 2024
Background: Vulvar lichen sclerosus (VLS) is a chronic inflammatory skin condition associated with significant impairment of quality of life and potential risk of malignant transformation. However, diagnosis of VLS is often delayed due to its variable clinical presentation and shame-related late consultation. Machine learning (ML)-trained image recognition software could potentially facilitate early diagnosis of VLS.
View Article and Find Full Text PDFAI image classification algorithms have shown promising results when applied to skin cancer detection. Most public skin cancer image datasets are comprised of dermoscopic photos and are limited by selection bias, lack of standardization, and lend themselves to development of algorithms that can only be used by skilled clinicians. The SLICE-3D ("Skin Lesion Image Crops Extracted from 3D TBP") dataset described here addresses those concerns and contains images of over 400,000 distinct skin lesions from seven dermatologic centers from around the world.
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- The study explores how well two commercial convolutional neural networks (CNNs) assess melanoma risk in real-world dermoscopic images compared to experienced dermatologists.* -
- Conducted at the University Hospital Basel, the research involved analyzing 117 image sets of skin lesions to compare and evaluate the assessment reliability between the two CNNs using variation and correlation metrics.* -
- Results showed that CNN-1 was more consistent in identifying clinically benign lesions with cancerous risk, while CNN-2 excelled with benign-scored lesions; both struggled with lesions that had conflicting risk assessments.*
Hand eczema (HE) is one of the most frequent dermatoses, known to be both relapsing and remitting. Regular and precise evaluation of the disease severity is key for treatment management. Current scoring systems such as the hand eczema severity index (HECSI) suffer from intra- and inter-observer variance.
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