Journal of the European Academy of Dermatology and Venereology




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Issue Information

doi : 10.1111/jdv.19207

Journal of the European Academy of Dermatology and Venereology: Volume 38, Issue 12

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Developments in digital intelligence for dermatology

doi : 10.1111/jdv.20353

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Artificial intelligence: A new frontier in dermatology

doi : 10.1111/jdv.20299

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Decoding the ABCs of natural language processing in dermatology

doi : 10.1111/jdv.20381

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From promise to practice: Artificial intelligence in skin cancer screenings

doi : 10.1111/jdv.20376

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Virtual reality-driven skin checks may be a promising tool in dermatology digital education

doi : 10.1111/jdv.20390

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Leveraging artificial intelligence to pursue treatment personalization in atopic dermatitis

doi : 10.1111/jdv.20361

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Weak supervision, strong results: Automating melanocyte lesion diagnosis with deep learning

doi : 10.1111/jdv.20382

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Will artificial intelligence be the answer for the gap in vulvovaginal diseases?

doi : 10.1111/jdv.20355

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Will AI revolutionize literature reviews?

doi : 10.1111/jdv.20354

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Insights into AI and facial ageing

doi : 10.1111/jdv.20401

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Skinformatics: Navigating the big data landscape of dermatology

doi : 10.1111/jdv.20319

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Natural language processing in dermatology: A systematic literature review and state of the art

doi : 10.1111/jdv.20286

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Appraisal of AI-generated dermatology literature reviews

doi : 10.1111/jdv.20237

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Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study

doi : 10.1111/jdv.19905

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Weakly supervised deep learning image analysis can differentiate melanoma from naevi on haematoxylin and eosin-stained histopathology slides

doi : 10.1111/jdv.20307

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New horizons in dermatological education: Skin cancer screening with virtual reality

doi : 10.1111/jdv.19960

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Human-multimodal deep learning collaboration in ‘precise’ diagnosis of lupus erythematosus subtypes and similar skin diseases

doi : 10.1111/jdv.20031

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AI-powered visual diagnosis of vulvar lichen sclerosus: A pilot study

doi : 10.1111/jdv.20306

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Residual facial erythema in atopic dermatitis patients treated with dupilumab stratified by machine learning

doi : 10.1111/jdv.19909

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Deep learning predicted perceived age is a reliable approach for analysis of facial ageing: A proof of principle study

doi : 10.1111/jdv.20365

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Comparison of artificial intelligence smartphone applications for skin cancer risk stratification of pigmented lesions: An observational study

doi : 10.1111/jdv.20253

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A new dawn for orphan diseases in dermatology: The transformative potential of digital twins

doi : 10.1111/jdv.20062

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Navigating dermatological care: Experience with assisted teledermatology practice on e-Sanjeevani platform

doi : 10.1111/jdv.20181

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The future of digital pills and their potential use in dermatological clinical trials

doi : 10.1111/jdv.20224

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Mobile teledermoscopy for patients at high risk of cutaneous melanoma: A single-arm, feasibility study of a clinical intervention at two tertiary centres (MOBILEMEL)

doi : 10.1111/jdv.20300

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Large language models and dermoscopy: Assessing the potential of task-specific GPT-4 vision in diagnosing basal cell carcinoma

doi : 10.1111/jdv.20333

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Impact of dermoscopy training associated with artificial intelligence on general practitioner residents

doi : 10.1111/jdv.20328

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Correction to ‘Assessing the dynamic changes in vitiligo: Reliability and validity of the Vitiligo Disease Activity Score (VDAS) and Vitiligo Disease Improvement Score (VDIS)’

doi : 10.1111/jdv.20364

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A special thank you to our reviewers!

doi : 10.1111/jdv.20405

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