Basic principles of artificial intelligence in dermatology explained using melanoma.

The use of artificial intelligence (AI) continues to establish itself in the most diverse areas of medicine at an increasingly fast pace. Nevertheless, many healthcare professionals lack the basic technical understanding of how this technology works, which severely limits its application in clinical settings and research. Thus, we would like to discuss the functioning and classification of AI using melanoma as an example in this review to build an understanding of the technology behind AI. For this purpose, elaborate illustrations are used that quickly reveal the technology involved. Previous reviews tend to focus on the potential applications of AI, thereby missing the opportunity to develop a deeper understanding of the subject matter that is so important for clinical application. Malignant melanoma has become a significant burden for healthcare systems. If discovered early, a better prognosis can be expected, which is why skin cancer screening has become increasingly popular and is supported by health insurance. The number of experts remains finite, reducing their availability and leading to longer waiting times. Therefore, innovative ideas need to be implemented to provide the necessary care. Thus, machine learning offers the ability to recognize melanomas from images at a level comparable to experienced dermatologists under optimized conditions.

Characteristics of dermatomyositis patients with and without associated malignancy.

BACKGROUND: Dermatomyositis belongs to the rare idiopathic, inflammatory myositis group. A previously postulated link between some cases of dermatomyositis and malignancy has been established in recent years. Criteria suggestive of a malignancy association are still being explored. PATIENTS AND METHODS: We retrospectively analyzed data from 63 patients with dermatomyositis over a period of 15 years. RESULTS: The following criteria argue for cancer-associated dermatomyositis: older age (> 52 years [P = 0.001], > 65 years [P = 0.002], ≥ 75 years [P = 0.002]), shorter time between manifestation and diagnosis of dermatomyositis (malignancy group: 59 days vs. non-malignancy group: 137 days [P = 0.022]), typical skin involvement such as Gottron sign (P = 0.045), centrofacial erythema (P = 0.036) and typical erythema on the upper arms and forearms (P = 0.019), oropharyngeal involvement (P = 0.015) and increased ALT (P = 0.031). The following criteria argue for non-cancer-associated dermatomyositis: younger age (≤ 52 years [P = 0.001], 40-65 years [P = 0.045]) and pruritus (P = 0.026). CONCLUSIONS: The aforementioned criteria have been documented in the literature, but reported findings are heterogenous concerning the suitability of their markers for malignancy association. Small study populations, few prospective controlled studies, summarization of different forms of myositis and inconsistent use nomenclature contribute to biased results. Our study aims to make an important contribution toward the identification of risk factors in cancer-associated dermatomyositis.

Charakteristika von Dermatomyositis-Patienten mit und ohne Malignom-Assoziation.

HINTERGRUND: Die Dermatomyositis gehört zur Gruppe der seltenen, idiopathischen, inflammatorischen Myositiden. Für die paraneoplastische Form der Dermatomyositis wurde in der Vergangenheit ein Zusammenhang mit Malignomen erkannt. Faktoren, die für eine Malignom-Assoziation sprechen, werden bis heute untersucht. PATIENTEN UND METHODIK: Es wurden retrospektiv über einen Zeitraum von 15 Jahren die Daten von 63 Patienten mit Dermatomyositis analysiert. ERGEBNISSE: Folgende Faktoren gaben einen Hinweis für eine Dermatomyositis mit Malignom-Assoziation: ein höheres Patientenalter (> 52 Jahre [P = 0,001], > 65 Jahre [P = 0,002], ≥ 75 Jahre [P = 0,002]), eine kürzere Zeit zwischen Erstmanifestation und Erstdiagnose (Malignom-Gruppe: 59 Tage vs. Nicht-Malignom-Gruppe: 137 Tage [P = 0,022]), eine Hautbeteiligung in Form von Gottron-Zeichen (P = 0,045), zentrofazialen Erythemen (P = 0,036) oder typischen Erythemen an den Ober-/Unterarmen (P = 0,019), eine oropharyngeale Beteiligung (P = 0,015) und eine GPT-Erhöhung (P = 0,031). Folgende Faktoren sprachen eher gegen eine Malignom-Assoziation: ein jüngeres Patientenalter (≤ 52 Jahre [P = 0,001], 40-65 Jahre [P = 0,045]) und Juckreiz (P = 0,026). SCHLUSSFOLGERUNGEN: In der Literatur finden sich heterogene Ergebnisse zu den genannten Faktoren hinsichtlich ihrer Eignung als Marker für eine Malignom-Assoziation. Erschwert ist die Faktorenfindung aufgrund kleiner Studienpopulationen, wenigen prospektiven und kontrollierten Studien, die Einordnung von Populationen als Myositis-Patienten ohne Differenzierung und eine inkonsistente Verwendung der Nomenklatur. Mit unserer Studie wollen wir einen wichtigen Beitrag zur Identifizierung von Risikofaktoren bei Dermatomyositis mit Malignom-Assoziation leisten.

Pathophysiological basis of systemic treatments in psoriasis.

Over the past 15 years, the spectrum of systemic antipsoriatic treatments has dramatically expanded. Until the end of the last millennium, systemic therapy had been restricted to four oral agents: methotrexate, cyclosporine, acitretin, and fumaric acid esters. Today, there are additionally seven biologics and one new oral antipsoriatic drug, as well as the first available biosimilars. Six more biologics with novel target structures and at least four biosimilars are currently being developed (phase III). This progress has been based on new insights into the pathogenesis of psoriasis, in which tumor necrosis factor and especially Th17 immune responses with their associated cytokines interleukin 23 and 17 play a key role. The development of new-generation biologics as well as immunomodulatory small molecules can be attributed to these pathophysiological findings. Phosphodiesterase 4 inhibitors, dimethyl fumarate, and Janus kinase inhibitors all interact with Th17 immune responses. Some of these drugs are in advanced clinical development and are also beneficial in psoriatic arthritis. Today, psoriasis and psoriatic arthritis therefore rank among the most readily treatable inflammatory autoimmune disorders. Dermatology is increasingly becoming a specialty of modern targeted immunotherapies.