The British journal of dermatology
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In the past, the skills required to make an accurate dermatological diagnosis have required exposure to thousands of patients over many years. However, in recent years, artificial intelligence (AI) has made enormous advances, particularly in the area of image classification. This has led computer scientists to apply these techniques to develop algorithms that are able to recognize skin lesions, particularly melanoma. ⋯ The burden of skin cancer is growing within the Western world, with major implications for both population skin health and the provision of dermatology services. AI has the potential to assist in the diagnosis of skin lesions and may have particular value at the interface between primary and secondary care. The emerging technology represents an exciting opportunity for dermatologists, who are the individuals best informed to explore the utility of this powerful novel diagnostic tool, and facilitate its safe and ethical implementation within healthcare systems.
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Skin cancer is the commonest malignancy worldwide, often occurring on the face. Both the condition and treatment can lead to scarring and facial disfigurement, affecting a patient's health-related quality of life (HRQoL), which can be measured using patient-reported outcome measures (PROMs). ⋯ This systematic review critically appraises PROMs for facial skin cancer using internationally accepted criteria. The identified PROMs demonstrate a variation in the quality of validation performed, with a need to improve this across all PROMs in the field. Only through improving the quality of available PROMs and their focus on the post-treatment aesthetic and functional outcome will we be able to truly appreciate the concerns of our patients and improve the management of facial skin cancer.
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Skin cancer is the commonest malignancy worldwide, often occurring on the face. Both the condition and treatment can lead to scarring and facial disfigurement, affecting a patient's health-related quality of life (HRQoL), which can be measured using patient-reported outcome measures (PROMs). ⋯ This systematic review critically appraises PROMs for facial skin cancer using internationally accepted criteria. The identified PROMs demonstrate a variation in the quality of validation performed, with a need to improve this across all PROMs in the field. Only through improving the quality of available PROMs and their focus on the post-treatment aesthetic and functional outcome will we be able to truly appreciate the concerns of our patients and improve the management of facial skin cancer.
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Diagnostic errors are the most common, costly and dangerous of medical mistakes. In part 1 of this series, we described how general and dermatology-specific cognitive and perceptual biases underlie most of our correct diagnoses, as well as being a source of diagnostic medical errors. ⋯ Current individual and medical cultural attitudes need to be modified in order to incorporate improvements in diagnosis. Algorithms, artificial intelligence and system changes are being developed to address error and improve diagnostic accuracy.
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Meta Analysis Comparative Study
Conventional and combination topical photodynamic therapy for basal cell carcinoma: systematic review and meta-analysis.
Topical photodynamic therapy (PDT) is an established treatment option for low-risk basal cell carcinoma (BCC). ⋯ PDT is an effective treatment for low-risk BCC, with excellent cosmesis and safety. Imiquimod has higher efficacy than single-cycle PDT but more adverse effects. Highest efficacy is with excisional surgery. Fractionated and combination PDT options warrant further study.