{"id":49640,"date":"2021-02-19T18:57:37","date_gmt":"2021-02-19T17:57:37","guid":{"rendered":"https:\/\/blogs.bmj.com\/bmj\/?p=49640"},"modified":"2021-02-19T20:04:11","modified_gmt":"2021-02-19T19:04:11","slug":"what-role-could-art-play-in-improving-visual-literacy-in-dermatology","status":"publish","type":"post","link":"https:\/\/blogs.bmj.com\/bmj\/2021\/02\/19\/what-role-could-art-play-in-improving-visual-literacy-in-dermatology\/","title":{"rendered":"What role could art play in improving visual literacy in dermatology?\u00a0"},"content":{"rendered":"<p><span style=\"font-weight: 400\">Dermatology has evolved over the years, but the common thread remains visual literacy. Visual literacy is the learning, understanding, and interpretation of images by the observer. [<\/span><span style=\"font-weight: 400\">1]<\/span><span style=\"font-weight: 400\"> Visual literacy is key to the observation of art and the effectiveness of artificial intelligence systems in dermatology.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Dermatology is a visual specialty that relies on pattern recognition to make a diagnosis. These visual skills may be enhanced by understanding and appreciating art. As part of their training, dermatology residents in the US, took an art appreciation course at the museum of arts in Boston. [<\/span><span style=\"font-weight: 400\">2] <\/span><span style=\"font-weight: 400\">Students were given both clinical and art images to interpret before and after the course and results showed an improvement in visual diagnostic skills. Similar pilot studies have been trialled in the U.K<\/span><span style=\"font-weight: 400\"> with a perceived improvement in visual skills by participants. [3,4] Reflection also improved, which in medicine is key when evaluating a new patient.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">As dermatologists, we look at a patient, pause and consider the history and investigations, and look again to make a differential diagnosis. Experienced art observers often do not accept their first impression of an image, but examine the work in context of the artist\u2019s style, the name, and backstory of a piece of art, before making their final interpretation. For example, Edward Hoppers\u2019 famous \u201cNighthawks\u201d painting is a vision of New York in the 1940s. [<\/span><span style=\"font-weight: 400\">5] <\/span><span style=\"font-weight: 400\">On first impressions, the painting may be interpreted as moody and uninteresting, but in context of the title, knowledge of Hoppers\u2019 style, closer inspection of individual figures and the dramatic contrast with light and shade; a more powerful, intriguing and possibly ominous piece can be seen. However, the visual literacy of a painting can be subjective, as can the visual literacy by a dermatologist and a patient with skin disease.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">The use of artificial intelligence in medicine is potentially ground-breaking and is particularly relevant to those specialties that rely on pattern recognition to make a diagnosis. Artificial intelligence systems have successfully been trialled in radiology, oncology, ophthalmology, and gastroenterology to aid diagnosis. It is hardly surprising that dermatology, a visual specialty; clinically, dermatoscopically, and histologically, lends itself to this technology.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">Artificial intelligence systems are based on artificial neural networks which represent the workings of the normal brain. Huge amounts of labelled data (ground truth) are fed into the neural networks, which learn, extract information from the images, and produce algorithms in order to independently make decisions on classification of new images. This is a form of visual literacy by the artificial intelligence system; they have learnt patterns which distinguish images and are able to make independent diagnoses due to this learned behaviour. However, the precision of an artificial intelligence system is based on the accuracy and amount of data inputted. For example, one could confidently teach an artificial intelligence system to distinguish melanomas from benign naevi, as large datasets of images are achievable, but it will be difficult to teach an artificial intelligence system to diagnose rare skin cancers with only a limited bank of images. Humans can see an image once or twice and remember it forever.<\/span><\/p>\n<p><span style=\"font-weight: 400\">Skin cancer has risen by 20% per year for the last decade in the UK<\/span><span style=\"font-weight: 400\"> and this demand is overwhelming many dermatology departments. [6] Detection of skin cancers is an obvious focus for artificial intelligence in dermatology. Research has shown that artificial neural networks can be as accurate as 21 dermatologists in diagnosing benign and malignant skin lesions. [<\/span><span style=\"font-weight: 400\">7] <\/span><span style=\"font-weight: 400\">Further research showed that artificial intelligence outperformed dermatologists in diagnosing benign and malignant skin lesions. [<\/span><span style=\"font-weight: 400\">8]<\/span><span style=\"font-weight: 400\"> These findings could result in a potential solution to the two week wait skin cancer crisis.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">However, the question arises, whether artificial intelligence systems could be developed which are able to diagnose the more complex or rare disorders. Takayasu\u2019s Arteritis presenting with fevers, aortic regurgitation, and skin necrosis may require input from multiple specialties and numerous investigations before the diagnosis can be reached. [<\/span><span style=\"font-weight: 400\">9]<\/span><span style=\"font-weight: 400\"> In addition, images of skin disease in Fitzpatrick darker skin types IV-VI are limited, and unless an Artificial Intelligence system is trained with the appropriate &#8220;ground truth,&#8221; diagnostic accuracy would be affected. However, there is a growing body of literature in ethnic dermatology, <\/span><span style=\"font-weight: 400\">which aims to improve both the clinician\u2019s diagnostic skills as well as Artificial Intelligence systems. [10]<\/span><\/p>\n<p><span style=\"font-weight: 400\">As clinicians, we have an emotional quest to make the right diagnosis for our patients and make them better. Artificial intelligence systems in dermatology do not have this emotional connection and their diagnoses are based on visual images alone. The dermatologist should not fear replacement by artificial intelligence technology, but view this advance as augmented intelligence, where man and machine assist each other to improve patient care. The universal rapid growth of artificial intelligence is inevitable and exciting, but there needs to be better understanding of both accuracy and accountability before it reaches the clinic.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400\">Visual literacy is integral to the dermatologist. It is a human skill that can be heightened by understanding and appreciating art. Artificial intelligence may attempt to learn it, but is unlikely to be able to replicate the skill completely. The modern dermatologist would benefit from improving their visual literacy, but should also embrace the many benefits that will come from artificial intelligence.\u00a0<\/span><\/p>\n<p><em><span style=\"font-weight: 400\"><strong>Monika Saha<\/strong>, consultant dermatologist, Lewisham and Greenwich NHS Trust<\/span><\/em><\/p>\n<p><em><span style=\"font-weight: 400\"><strong>Mo Saha<\/strong>, c<\/span><span style=\"font-weight: 400\">reative Strategy Partner of WorkSmiths, a brand and innovation studio London.<\/span><\/em><\/p>\n<p><em><strong>Competing interests<\/strong>: none declared.\u00a0<\/em><\/p>\n<p><strong>References:<\/strong><\/p>\n<ol>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Debes JL. The loom of visual literacy- an overview. Audiovisual Instr 1969; 14,8, 25-27<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Zimmerman C, Huang TJ, Buzney EA. Refining the eye: Dermatology and visual literacy. J of Museum Education 2016; 41: 116-122<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Griffin LL, Chiang NYZ, Tomlin H et all. A visual literacy course for dermatology trainees. Br. J Dermatol. 2017;177 (1): 310-311.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Gardham N, Walsh S. Comment on \u2018A visual literacy course for dermatology trainees. Br J Dermatol 2018;178(2):572-573.\u00a0<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">https:\/\/en.wikipedia.org\/wiki\/Nighthawks_(painting)<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Eedy D. The crisis in dermatology. BMJ 2015;350:h2765.<\/span><\/li>\n<li style=\"font-weight: 400\">Esteva A, Kuprel B, Novoa RA et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature 2017; 542 (7639): 115-118.<\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Brinker TJ, Hekler A, Enk AH et al. Deep learning outperformed 136 of 157 dermatologists in a head-to head dermoscopic melanoma image classification task. Eur J Cancer 2019. 113:47-54.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\">Estfan Y, D\u2019Cruz DP, Patel S et al. An unusual and potentially fatal cause of scalp crusting. Clin Exp Dermatol 2017; 42(4): 441-443.<\/span><\/li>\n<li style=\"font-weight: 400\">https:\/\/www.theguardian.com\/world\/2020\/aug\/24\/dermatology-has-come-a-long-way-in-confronting-its-historical-eurocentric-bias<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Dermatology has evolved over the years, but the common thread remains visual literacy. Visual literacy is the learning, understanding, and interpretation of images by the observer. [1] Visual literacy is [&#8230;]<\/p>\n<p><a class=\"btn btn-secondary understrap-read-more-link\" href=\"https:\/\/blogs.bmj.com\/bmj\/2021\/02\/19\/what-role-could-art-play-in-improving-visual-literacy-in-dermatology\/\">More&#8230;<\/a><\/p>\n","protected":false},"author":66,"featured_media":49643,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[223],"tags":[],"class_list":["post-49640","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-guest-bloggers"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What role could art play in improving visual literacy in dermatology?\u00a0 - The BMJ<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blogs.bmj.com\/bmj\/2021\/02\/19\/what-role-could-art-play-in-improving-visual-literacy-in-dermatology\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What role could art play in improving visual literacy in dermatology?\u00a0 - The BMJ\" \/>\n<meta property=\"og:description\" content=\"Dermatology has evolved over the years, but the common thread remains visual literacy. 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Visual literacy is the learning, understanding, and interpretation of images by the observer. 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