AI Medical Compendium Journal:
Journal of the European Academy of Dermatology and Venereology : JEADV

Showing 11 to 20 of 28 articles

Consistency of convolutional neural networks in dermoscopic melanoma recognition: A prospective real-world study about the pitfalls of augmented intelligence.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Deep-learning convolutional neural networks (CNNs) have outperformed even experienced dermatologists in dermoscopic melanoma detection under controlled conditions. It remains unexplored how real-world dermoscopic image transformations aff...

An open source pipeline for quantitative immunohistochemistry image analysis of inflammatory skin disease using artificial intelligence.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: The application of artificial intelligence (AI) to whole slide images has the potential to improve research reliability and ultimately diagnostic efficiency and service capacity. Image annotation plays a key role in AI and digital patholo...

Accuracy and clinical relevance of an automated, algorithm-based analysis of facial signs from selfie images of women in the United States of various ages, ancestries and phototypes: A cross-sectional observational study.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Real-life validation is necessary to ensure our artificial intelligence (AI) skin diagnostic tool is inclusive across a diverse and representative US population of various ages, ancestries and skin phototypes.

Deep learning-based classification of dermatological lesions given a limited amount of labelled data.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Artificial intelligence (AI) techniques are promising in early diagnosis of skin diseases. However, a precondition for their success is the access to large-scaled annotated data. Until now, obtaining this data has only been feasible with ...

Artificial intelligence for the automated single-shot assessment of psoriasis severity.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: PASI score is globally used to assess disease activity of psoriasis. However, it is relatively complicated and time-consuming, and the score will vary due to the inconsistent subjectivity between dermatologists. Therefore, an AI system ca...

An objective skin-type classification based on non-invasive biophysical parameters.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Despite the invention of various non-invasive bioengineering tools, skin-type analysis has largely been based on subjective assessments. However, advancements in the functional cosmetic industry and artificial intelligence-assisted dermat...

Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and for about 10-20% of the tumours affecting the head and neck area. Radiotherapy is suggested for localized cutaneous squamous cell carcinomas (cSCC) wit...