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Challenges of COVID‐19 pandemic for dermatology [PDF]
Dermatologic Therapy, 2020 Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a new coronavirus responsible for the pandemic named coronavirus disease 2019 (COVID‐19). The disease causes SARS with a significant morbidity and mortality. We provide a review with a focus
Uwe Wollina
openalex +2 more sources
Disparities in dermatology AI performance on a diverse, curated clinical image set [PDF]
Science Advances, 2021 An estimated 3 billion people lack access to dermatological care globally. Artificial intelligence (AI) may aid in triaging skin diseases and identifying malignancies.
R. Daneshjou +16 more
semanticscholar +1 more source
General dermatology and dermatology in primary healthcare
Clinical and Experimental DermatologyA woman in her 40s with recurrent urticarial-like rash, low-grade fever, fatigue and lower limb pain was diagnosed with Schnitzler syndrome after laboratory results revealed elevated inflammatory markers and monoclonal IgM gammopathy. Histopathology showed neutrophilic infiltrates, and imaging identified osteosclerotic lesions.
Bučić, Dinea +2 more
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A Review on the Safety of Using JAK Inhibitors in Dermatology: Clinical and Laboratory Monitoring
Dermatologic Therapy, 2023 Janus kinase (JAK) inhibitors are disease-modifying agents with efficacy in treating a spectrum of burdensome dermatologic conditions. The US Food and Drug Administration (FDA) recently placed a black box warning on this class of medications due to ...
Christeen Samuel +3 more
semanticscholar +1 more source
Clincal and Experimental Dermatology, 2023 BACKGROUND The global use of artificial intelligence has the potential to revolutionize the healthcare industry. Despite the fact that artificial intelligence is becoming more popular, there is still a lack of evidence on its use in dermatology ...
Miłosz Lewandowski +3 more
semanticscholar +1 more source
Principles, applications, and future of artificial intelligence in dermatology
Frontiers in Medicine, 2023 This paper provides an overview of artificial-intelligence (AI), as applied to dermatology. We focus our discussion on methodology, AI applications for various skin diseases, limitations, and future opportunities.
J. Omiye +4 more
semanticscholar +1 more source
Artificial Intelligence in Dermatology Image Analysis: Current Developments and Future Trends
Journal of Clinical Medicine, 2022 Background: Thanks to the rapid development of computer-based systems and deep-learning-based algorithms, artificial intelligence (AI) has long been integrated into the healthcare field.
Zhouxiao Li +5 more
semanticscholar +1 more source
Artificial Intelligence in Dermatology: Challenges and Perspectives
Dermatologic Therapy, 2022 Artificial intelligence (AI) based on machine learning and convolutional neuron networks (CNN) is rapidly becoming a realistic prospect in dermatology.
K. Liopyris +3 more
semanticscholar +1 more source
Racial disparities in dermatology
Archives of Dermatological Research, 2022 Significant racial/ethnic disparities in dermatologic care and their subsequent impact on dermatologic conditions were recently reported. Contributing factors include socioeconomic factors, gaps in educational exposure, and underrepresentation of ...
S. Narla +3 more
semanticscholar +1 more source
JAMA dermatology, 2021 Importance The use of artificial intelligence (AI) is accelerating in all aspects of medicine and has the potential to transform clinical care and dermatology workflows.
R. Daneshjou +18 more
semanticscholar +1 more source