"Skin cancer screening"

No abstract text is available yet for this article.

BACKGROUND: Preventive care is important for managing inflammatory bowel disease (IBD), yet primary care providers (PCPs) often face challenges in delivering such care due to discomfort and unfamiliarity with IBD-specific guidelines. This study aims to assess PCPs' attitudes towards, and practices in, providing preventive screenings for IBD patients, highlighting areas for improvement in guideline dissemination and education. METHODS: Using a web-based opt-in panel of PCPs (DocStyles survey, spring 2022), we assessed PCPs' comfort level with providing/recommending screenings and the reasons PCPs felt uncomfortable (n = 1,503)...

BACKGROUND AND OBJECTIVES: Due to increasing skin cancer incidence, Germany implemented a statutory nationwide routine skin cancer screening (rSCS) in 2008. The present study aims (1) to analyze which patient factors are associated with the participation in rSCS in Germany and (2) to investigate reasons for nonparticipation. PATIENTS AND METHODS: Participants and nonparticipants of rSCS (≥ 35 years) were recruited in routine care in nine dermatological outpatient clinics...

BACKGROUND AND OBJECTIVES: Due to increasing skin cancer incidence, Germany implemented a statutory nationwide routine skin cancer screening (rSCS) in 2008. The present study aims (1) to analyze which patient factors are associated with the participation in rSCS in Germany and (2) to investigate reasons for nonparticipation. PATIENTS AND METHODS: Participants and nonparticipants of rSCS (≥ 35 years) were recruited in routine care in nine dermatological outpatient clinics...

BACKGROUND AND AIM: Skin cancer is a major public health issue. While self-examinations and professional screenings are recommended, they are rarely performed. Mobile health (mHealth) apps utilising artificial intelligence (AI) for skin cancer screening offer a potential solution to aid self-examinations; however, their uptake is low. Therefore, the aim of this research was to examine provider and user characteristics influencing people's decisions to seek skin cancer screening performed by a mHealth app or a dermatologist...

Melanoma is the leading cause of skin cancer-related deaths. Yet, early detection remains the most cost-effective means of preventing death from melanoma. Early detection can be achieved by a physician and/or the patient (also known as a self-skin exam). Skin exams performed by physicians are further enhanced using dermoscopy. Dermoscopy is a non-invasive technique that allows for the visualization of subsurface structures that are otherwise not visible to the naked eye. Evidence demonstrates that dermoscopy improves the diagnostic accuracy for skin cancer, including melanoma; it decreases the number of unnecessary skin biopsies of benign lesions and improves the benign-to-malignant biopsy ratio...

BACKGROUND: whether screening for skin cancer affects melanoma-specific mortality in a population-based setting remains unclear. METHODS: in this population-based cohort study, we characterized and evaluated a skin cancer prevention program following a targeted screening approach conducted in 1989-1994 in the Austrian province Vorarlberg, with follow-up until 2019. The general population and attendees of a health examination program served for comparison. RESULTS: in the screening program including full follow-up until 2019, 207 invasive and 187 in situ melanomas were identified in 8997 individuals...

No abstract text is available yet for this article.

Artificial intelligence is poised to rapidly reshape many fields, including that of skin cancer screening and diagnosis, both as a disruptive and assistive technology. Together with the collection and availability of large medical data sets, artificial intelligence will become a powerful tool that can be leveraged by physicians in their diagnoses and treatment plans for patients. This comprehensive review focuses on current progress toward AI applications for patients, primary care providers, dermatologists, and dermatopathologists, explores the diverse applications of image and molecular processing for skin cancer, and highlights AI's potential for patient self-screening and improving diagnostic accuracy for non-dermatologists...

IMPORTANCE: Total body photography for skin cancer screening is a well-established tool allowing documentation and follow-up of the entire skin surface. Artificial intelligence-based systems are increasingly applied for automated lesion detection and diagnosis. DESIGN AND PATIENTS: In this prospective observational international multicentre study experienced dermatologists performed skin cancer screenings and identified clinically relevant melanocytic lesions (CRML, requiring biopsy or observation)...

BACKGROUND: Technological advances in the field of virtual reality (VR) offer new opportunities in many areas of life, including medical education. The University of Münster has been using VR scenarios in the education of medical students for several years, especially for situations that are difficult to reproduce in reality (e.g., brain death). Due to the consistently positive feedback from students, a dermatological VR scenario for skin cancer screening was developed. OBJECTIVES: Presentation and first evaluation of the skin cancer screening VR scenario to determine to what extent the technical implementation of the scenario was evaluated overall by the students and how their subjective competence to perform a skin cancer screening changed over the course of the teaching unit (theory seminar, VR scenario, theoretical debriefing)...

BACKGROUND: Non-melanoma skin cancer (NMSC) is highly prevalent in the United States, with darker-skinned patients (DSP) exhibiting lower incidence but increased morbidity and mortality. The purpose of this study is to elucidate NMSC disparities between DSP (Fitzpatrick skin phototype IV or more) and lighter-skinned patients (LSP, Fitzpatrick skin phototype III or less), focusing on surgical features of non-Mohs micrographic surgery-treated NMSC. METHODS: This retrospective cohort study included LSP and DSP diagnosed with either basal cell carcinoma (BCC) or squamous cell carcinoma (SCC) in an academic dermatology setting...

BACKGROUND: Artificial intelligence (AI) shows promising potential to enhance human decision-making as synergistic augmented intelligence (AuI), but requires critical evaluation for skin cancer screening in a real-world setting. OBJECTIVES: To investigate the perspectives of patients and dermatologists after skin cancer screening by human, artificial and augmented intelligence. METHODS: A prospective comparative cohort study conducted at the University Hospital Basel included 205 patients (at high-risk of developing melanoma, with resected or advanced disease) and 8 dermatologists...

BACKGROUND: More and more genetic and metabolic abnormalities are now known to cause cancer, which is typically deadly. Any bodily part may become infected by cancerous cells, which can be fatal. Skin cancer is one of the most prevalent types of cancer, and its prevalence is rising across the globe. Squamous and basal cell carcinomas, as well as melanoma, which is clinically aggressive and causes the majority of deaths, are the primary subtypes of skin cancer. Screening for skin cancer is therefore essential...

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...

No abstract text is available yet for this article.

BACKGROUND: The number of skin cancer cases and related deaths continues to increase worldwide, including in Portugal. The lack of efficient health care leaves the southern Portuguese population at risk of presenting skin lesions at later stages. An initiative for skin cancer screening and medical care follow-up was created by the nonprofit organization Liga Portuguesa Contra o Cancro - Núcleo Regional do Sul (LPCC-NRS). METHODS: Information was gathered from 4,398 participants in several Southern Portugal regions, from January 2021 to July 2022...

Correct classification of skin lesions is a key step in skin cancer screening, which requires high accuracy and interpretability. This paper proposes a multimodal method for differentiating various clinical forms of basal cell carcinoma and benign neoplasms that includes machine learning. This study was conducted on 37 neoplasms, including benign neoplasms and five different clinical forms of basal cell carcinoma. The proposed multimodal screening method combines diffuse reflectance spectroscopy, optical coherence tomography and high-frequency ultrasound...

BACKGROUND: There is great interest in using artificial intelligence (AI) to screen for skin cancer. This is fueled by a rising incidence of skin cancer and an increasing scarcity of trained dermatologists. AI systems capable of identifying melanoma could save lives, enable immediate access to screenings, and reduce unnecessary care and health care costs. While such AI-based systems are useful from a public health perspective, past research has shown that individual patients are very hesitant about being examined by an AI system...

Combining perceptual learning techniques with adaptive learning algorithms has been shown to accelerate the development of expertise in medical and STEM learning domains (Kellman & Massey, 2013; Kellman, Jacoby, Massey & Krasne, 2022). Virtually all adaptive learning systems have relied on simple accuracy data that does not take into account response bias, a problem that may be especially consequential in multi-category perceptual classifications. We investigated whether adaptive perceptual learning in skin cancer screening can be enhanced by incorporating signal detection theory (SDT) methods that separate sensitivity from criterion...