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February 2024 in “npj digital medicine” This study developed a deep-learning model using unannotated dermatology images from online forums, achieving 49.64% accuracy in classifying 22 skin diseases and 61.76% accuracy in detecting monkeypox, highlighting the potential of these images for skin disease diagnostics in China.
January 2021 in “arXiv (Cornell University)” This study found that self-supervised pretraining significantly improves accuracy in medical image classifiers for dermatology and chest X-ray tasks, outperforming supervised baselines and showing robustness to distribution shifts with limited labeled data.
March 2014 in “Oxford University Press eBooks” This narrative review explores the failure of fludalanine as an orally active antibiotic and highlights valuable insights into problem-solving strategies in drug discovery, without reporting new clinical results.
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October 2005 in “Experimental Dermatology” This review explores the role of Foxn1 in mammalian skin biology, discussing its influence on hair follicle function and the potential for further research to enhance understanding of epithelial differentiation.
This study examined the molecular communication in psoriasis cells, highlighting unique immune cell interactions and identifying new features of the hair follicle cell-psoriasis axis. It suggests the potential for targeted therapies at the single-cell level to improve psoriasis treatment.