Smartphone Mobile Application to Enhance Diagnosis of Skin Cancer: A Guide for the Rural Practitioner

Primary care physicians occupy a vital position to impact many devastating conditions, especially those dependent upon early diagnosis, such as skin cancer. Skin cancer is the most common cancer in the United States and despite improvements in skin cancer therapy, patients with a delay in diagnosis and advanced disease continue to have a grave prognosis. Due to a variety of barriers, advanced stages of skin cancer are more prominent in rural populations. In order to improve early diagnosis four things are paramount: increased patient participation in prevention methods, establishment of screening guidelines, increased diagnostic accuracy of malignant lesions, and easier access to dermatologists. Recent expansion in smartphone mobile application technology offers simple ways for rural practitioners to address these problems. More than 100,000 health related applications are currently available, with over 200 covering dermatology. This review will evaluate the newest and most useful of those applications offered to enhance the prevention and early diagnosis of skin cancer, particularly in the rural population

Artificial Intelligence in Skin Cancer: A Literature Review from Diagnosis to Prevention and Beyond

Artificial Intelligence (AI) in medicine is quickly expanding, offering significant potential benefits in diagnosis and prognostication. While concerns may exist regarding its implementation, it is important for dermatologists and dermatopathologists to collaborate with technical specialists to embrace AI as a tool for enhancing medical decision-making and improving healthcare accessibility. This is particularly relevant in melanocytic neoplasms, which continue to present challenges despite years of experience. Dermatology, with its extensive medical data and images, provides an ideal field for training AI algorithms to enhance patient care. Collaborative efforts between medical professionals and technical specialists are crucial in harnessing the power of AI while ensuring it complements and enhances the existing healthcare framework. By staying informed about AI concepts and ongoing research, dermatologists can remain at the forefront of this emerging field and leverage its potential to improve patient outcomes. In conclusion, AI holds great promise in dermatology, especially in the management and analysis of Skin cancer (SC). In this review we strive to introduce the concepts of AI and its association with dermatology, providing an overview of recent studies in the field, such as existing applications and future potential in dermatology

Exploring the Potential of Convolutional Neural Networks in Healthcare Engineering for Skin Disease Identification

Skin disorders affect millions of individuals worldwide, underscoring the urgency of swift and accurate detection for optimal treatment outcomes. Convolutional Neural Networks (CNNs) have emerged as valuable assets for automating the identification of skin ailments. This paper conducts an exhaustive examination of the latest advancements in CNN-driven skin condition detection. Within dermatological applications, CNNs proficiently analyze intricate visual motifs and extricate distinctive features from skin imaging datasets. By undergoing training on extensive data repositories, CNNs proficiently classify an array of skin maladies such as melanoma, psoriasis, eczema, and acne. The paper spotlights pivotal progressions in CNN-centered skin ailment diagnosis, encompassing diverse CNN architectures, refinement methodologies, and data augmentation tactics. Moreover, the integration of transfer learning and ensemble approaches has further amplified the efficacy of CNN models. Despite their substantial potential, there exist pertinent challenges. The comprehensive portrayal of skin afflictions and the mitigation of biases mandate access to extensive and varied data pools. The quest for comprehending the decision-making processes propelling CNN models remains an ongoing endeavor. Ethical quandaries like algorithmic predisposition and data privacy also warrant significant consideration. By meticulously scrutinizing the evolutions, obstacles, and potential of CNN-oriented skin disorder diagnosis, this critique provides invaluable insights to researchers and medical professionals. It underscores the importance of precise and efficacious diagnostic instruments in ameliorating patient outcomes and curbing healthcare expenditures

Omics sciences and precision medicine in melanoma

Background: This article provides an overview of the application of omics sciences in melanoma research. The name omics sciences refers to the large-scale analysis of biological molecules like DNA, RNA, proteins, and metabolites. Methods: In the course of this review, we have adopted a focu-sed research strategy, meticulously selecting the most pertinent and emblematic articles related to the topic. Our methodology included a systematic examination of the scientific literature to guarantee a thorough and precise synthesis of the existing sources. Results: With the advent of high-throughput technologies, omics have become an essential tool for understanding the complexity of melanoma. In this article, we discuss the different omics approaches used in melanoma research, including genomics, transcriptomics, proteomics, and metabolomics. We also highlight the major findings and insights gained from these studies, including the identification of new therapeutic targets and the development of biomarkers for diagnosis and prognosis. Finally, we discuss the challenges and future directions in omics-based melanoma research, including the integration of multiple omics data and the development of personalized medicine approaches. Conclusions: Overall, this article emphasizes the importance of omics science in advancing our understanding of melanoma and its potential for improving patient outcomes

Situación actual de la prevención del cáncer de piel: una revisión siste

Skin cancer deaths continue to rise despite the implementation of numerous preventive campaigns and programs. The aim of this systematic review was to evaluate reviews of primary and secondary skin cancer prevention strategies as reported over the past 10 years. We analyzed 63 systematic reviews and meta-analyses: 30 (46.6%) addressing primary interventions and 35 (55.6%) addressing secondary interventions. Two of the reviews covered both. The most widely reported primary prevention approaches were education programs (63.3%), followed by risk modeling to identify individuals at high risk for melanoma (17.6%), and the promotion of sunscreen use (11.8%). The most widely reported secondary prevention measures concerned imaging systems for early skin cancer detection (40%), smartphones and new technologies (22.9%), and visual diagnosis in population-based screening (17.4%). The most effective measures were primary prevention education programs to improve sun protection habits.La mortalidad por cáncer de piel continúa aumentando a pesar de las numerosas intervenciones dedicadas a su prevención. El objetivo de esta revisión es estudiar la situación de la prevención primaria y secundaria del cáncer de piel en los últimos 10 a˜nos. Se incluye un total de 63 revisiones, 30 (46,6%) revisiones incluyeron estrategias de prevención primaria y 35 (55,6%) de prevención secundaria, incorporando 2 de las revisiones información sobre ambos tipos de estrategias. Para la prevención primaria, las medidas más estudiadas fueron losprogramas educativos (63,3%), seguidos de la creación de modelos para identificar a personascon alto riesgo de desarrollar un melanoma (17,6%) y la promoción del uso de fotoprotectores(11,8%). Los sistemas de toma de imagen para el diagnóstico precoz del cáncer de piel (40%),seguidos por el empleo de smartphones y nuevas tecnologías (22,9%), así como el diagnósticovisual como cribado poblacional (17,4%), fueron las medidas de prevención secundaria másevaluadas. De todas las medidas revisadas, las estrategias de prevención primaria centradas enprogramas educativos para mejorar los hábitos de fotoprotección fueron las que resultaron másefectivas

Effect of a Clinical Evidence Technology on Patient Skin Disease Outcomes in Primary Care: A Cluster-Randomized Controlled Trial

Objective: Providers’ use of clinical evidence technologies (CETs) improves their diagnosis and treatment decisions. Despite these benefits, few studies have evaluated the impact of CETs on patient outcomes. Investigators evaluated the effect of one CET, VisualDx, on skin problem outcomes in primary care. Methods: The cluster-randomized controlled pragmatic trial was set in outpatient clinics at an academic medical center in the Northeast. Participants were Primary Care Providers (PCPs) and adult patients seen for skin problems. The intervention was VisualDx as used by PCPs. Outcomes were patient-reported time from index clinic visit to problem resolution, and the number of follow-up visits to any provider for the same problem. PCPs assigned to intervention agreed to use VisualDx as their primary evidence source for skin problems. Control group PCPs agreed not to use VisualDx. Investigators collected outcome data from patients by phone at 30 day intervals. Cox proportional hazards models assessed time to resolution. Wilcoxon-rank sum tests and logistic regression compared return appointments. Results: Thirty-two PCPs and 433 patients participated. In proportional hazards modelling adjusted for provider clusters, the days from index visit to skin problem resolution were similar in both groups (HR 0.92; CI 0.70, 1.21 P= 0.54). Patient follow-up appointments did not differ significantly between groups (OR 1.26 95% CI 0.94, 1.70 P =0.29). Conclusion: This pragmatic trial tested the effectiveness of VisualDx on patient reported skin disease outcomes in a generalizable clinical setting. There was no difference in skin problem resolution or number of follow-up visits when PCPs used VisualDx