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Clinics in Dermatology Jun 2024Melanoma is the deadliest skin cancer, presenting typically with changing pigmented areas and usually treated with surgical removal. As benign cutaneous pigmented...
Melanoma is the deadliest skin cancer, presenting typically with changing pigmented areas and usually treated with surgical removal. As benign cutaneous pigmented lesions are very common in all populations, it can be challenging to identify which areas should be cut out or left untreated. Delayed treatment in melanoma increases the risk of death, but it is not possible to remove all lesions. Dermatoscopy uses polarised light and can be used to help distinguish melanomas from benign lesions. Dermatoscopy images with a confirmed diagnosis can be utilized to develop artificial intelligence as a medical device (AIaMD) tool. This contribution discusses the utilization of artificial intelligence (AI) in melanoma management and describes an AIaMD tool that has been used in current UK clinical practice on over 80,000 patients. This is a springboard for discussing the scope, risks, and mitigations for future AI use by all clinicians involved in managing people with melanoma.
PubMed: 38942155
DOI: 10.1016/j.clindermatol.2024.06.015 -
Indian Journal of Dermatology 2023The skin aging which entails modifications in the entire skin and skin support system is caused as a result of complex blend of intrinsic and extrinsic factors. The main... (Review)
Review
The skin aging which entails modifications in the entire skin and skin support system is caused as a result of complex blend of intrinsic and extrinsic factors. The main objective of this review is to provide critical insights into the effect of the aging determinants (intrinsic and extrinsic) on aging skin and to focus on a few classes of natural bioactives that were reported to counteract symptoms of cutaneous aging, pose potential, and beneficial health effect on aging skin supported with relevant scientific evidence. The narrative review of this cutaneous antiaging study incorporating the literature findings was retrieved from the search of computerized databases PubMed and Scopus, hand searches, and authoritative books. The antiaging skin care approach of using bioactives are basically nutritional hormetins, available from our natural heritage, identified as potent free radical scavengers, antioxidants, moisturizers, cell repairing agents, and ultraviolet protectives which have started to seek considerable attention among researchers and consumers due to the undesirable effect of chemical-based constituents on human health and environment. With the booming antiaging strategies, beauty has become the prime factor in considering one's health and overall "wellness". As promoting healthy aging is essential, the objective of aesthetic dermatology should shift from cosmetic interventions to the betterment of quality of life of aging society. The paper also discusses on certain artificial learning/machine-based algorithms, useful in screening of bioactive ingredients, helpful in developing of more tailored formulations. This narrative overview on skin antiaging natural bioactives and artificial learning-based bioactive screening approaches contributes for the improvement in dermatological drug discovery, in the development of novel targeted lead compounds and accelerates aging research and pharmaceutical research.
PubMed: 37822379
DOI: 10.4103/ijd.ijd_932_22 -
Frontiers in Medicine 2023This paper provides an overview of artificial-intelligence (AI), as applied to dermatology. We focus our discussion on methodology, AI applications for various skin... (Review)
Review
This paper provides an overview of artificial-intelligence (AI), as applied to dermatology. We focus our discussion on methodology, AI applications for various skin diseases, limitations, and future opportunities. We review how the current image-based models are being implemented in dermatology across disease subsets, and highlight the challenges facing widespread adoption. Additionally, we discuss how the future of AI in dermatology might evolve and the emerging paradigm of large language, and multi-modal models to emphasize the importance of developing responsible, fair, and equitable models in dermatology.
PubMed: 37901399
DOI: 10.3389/fmed.2023.1278232 -
Clinics in Dermatology 2024The integration of artificial intelligence (AI) in dermatology holds promise for enhancing clinical accuracy, enabling earlier detection of skin malignancies, suggesting... (Review)
Review
The integration of artificial intelligence (AI) in dermatology holds promise for enhancing clinical accuracy, enabling earlier detection of skin malignancies, suggesting potential management of skin lesions and eruptions, and promoting improved continuity of care. AI implementation in dermatology, however, raises several ethical concerns. This review explores the current benefits and challenges associated with AI integration, underscoring ethical considerations related to autonomy, informed consent, and privacy. We also examine the ways in which beneficence, nonmaleficence, and distributive justice may be impacted. Clarifying the role of AI, striking a balance between security and transparency, fostering open dialogue with our patients, collaborating with developers of AI, implementing educational initiatives for dermatologists and their patients, and participating in the establishment of regulatory guidelines are essential to navigating ethical and responsible AI incorporation into dermatology.
Topics: Artificial Intelligence; Humans; Dermatology; Informed Consent; Personal Autonomy; Privacy
PubMed: 38401700
DOI: 10.1016/j.clindermatol.2024.02.003 -
British Dental Journal Apr 2024
Topics: Humans; Skin Neoplasms; Artificial Intelligence
PubMed: 38671091
DOI: 10.1038/s41415-024-7364-1 -
Advances in Wound Care Oct 2023Tissue-engineered artificial skin for clinical reconstruction can be regarded as an established practice. Bi-layered skin equivalents are available as established...
Tissue-engineered artificial skin for clinical reconstruction can be regarded as an established practice. Bi-layered skin equivalents are available as established allogenic or autologous therapy, and various acellular skin replacements can support tissue repair. Moreover, there is considerable commonality between the skin and other soft tissue reconstruction products. This article presents an attempt to create a comprehensive global landscape review of advanced replacement materials and associated strategies for skin and soft tissue reconstruction. There has been rapid growth in the number of commercial and pre-commercial products over the past decade. In this survey, 263 base products for advanced skin therapy have been identified, across 8 therapeutic categories, giving over 350 products in total. The largest market is in the United States, followed by the E.U. zone. However, despite these advances, and the investment of resources in each product development, there are key issues concerning the clinical efficacy, cost-benefit of products, and clinical impact. Each therapeutic strategy has relative merits and limitations. A critical consideration in developing and evaluating products is the therapeutic modality, associated regulatory processes, and the potential for clinical adoption geographically, determined by regulatory territory, intellectual property, and commercial distribution factors. The survey identifies an opportunity for developments that improve basic efficacy or cost-benefit. The economic pressures on health care systems, compounded by the demands of our increasingly ageing population, and the imperative to distribute effective health care, create an urgent global need for effective and affordable products.
Topics: Skin, Artificial; Tissue Engineering; Skin; Wound Healing; Skin Transplantation
PubMed: 36680749
DOI: 10.1089/wound.2022.0050 -
International Journal of Dermatology Apr 2024Artificial intelligence (AI) uses algorithms and large language models in computers to simulate human-like problem-solving and decision-making. AI programs have recently... (Review)
Review
Artificial intelligence (AI) uses algorithms and large language models in computers to simulate human-like problem-solving and decision-making. AI programs have recently acquired widespread popularity in the field of dermatology through the application of online tools in the assessment, diagnosis, and treatment of skin conditions. A literature review was conducted using PubMed and Google Scholar analyzing recent literature (from the last 10 years through October 2023) to evaluate current AI programs in use for dermatologic purposes, identifying challenges in this technology when applied to skin of color (SOC), and proposing future steps to enhance the role of AI in dermatologic practice. Challenges surrounding AI and its application to SOC stem from the underrepresentation of SOC in datasets and issues with image quality and standardization. With these existing issues, current AI programs inevitably do worse at identifying lesions in SOC. Additionally, only 30% of the programs identified in this review had data reported on their use in dermatology, specifically in SOC. Significant development of these applications is required for the accurate depiction of darker skin tone images in datasets. More research is warranted in the future to better understand the efficacy of AI in aiding diagnosis and treatment options for SOC patients.
Topics: Humans; Algorithms; Artificial Intelligence; Dermatology; Skin Pigmentation; Technology; Racial Groups
PubMed: 38444331
DOI: 10.1111/ijd.17076 -
Journal of the Mechanical Behavior of... Nov 2023Understanding of the mechanical properties of skin is crucial in evaluating the performance of skin-interfacing medical devices. Artificial skin models (ASMs) have...
Understanding of the mechanical properties of skin is crucial in evaluating the performance of skin-interfacing medical devices. Artificial skin models (ASMs) have rapidly gained attention as they are able to overcome the challenges in ethically sourcing consistent and representative ex vivo animal or human tissue models. Although some ASMs have become commercialised, a thorough understanding of the mechanical properties of the skin models is crucial to ensure that they are suitable for the purpose of the study. In the present study, skin and fat layers of ASMs (Simulab, LifeLike, SynDaver and Parafilm) were mechanically characterised through hardness, needle insertion, tensile and compression testing. Different boundary constraint conditions (minimally and highly constrained) were investigated for needle insertion testing, while anisotropic properties of the skin models were investigated through different specimen orientations during tensile testing. Analysis of variance (ANOVA) tests were performed to compare the mechanical properties between the skin models. Properties of the skin models were compared against literature to determine the suitability of the skin models based on the material property of interest. All skin models offer relatively consistent mechanical performance, providing a solid basis for benchtop evaluation of skin-interfacing medical device performance. Through prioritising models with mechanical properties that are consistent with human skin data, and with limited variance, researchers can use the data presented here as a toolbox to select the most appropriate ASM for their particular application.
PubMed: 37717289
DOI: 10.1016/j.jmbbm.2023.106090 -
Life (Basel, Switzerland) Apr 2024Immuno-correlated dermatological pathologies refer to skin disorders that are closely associated with immune system dysfunction or abnormal immune responses.... (Review)
Review
Immuno-correlated dermatological pathologies refer to skin disorders that are closely associated with immune system dysfunction or abnormal immune responses. Advancements in the field of artificial intelligence (AI) have shown promise in enhancing the diagnosis, management, and assessment of immuno-correlated dermatological pathologies. This intersection of dermatology and immunology plays a pivotal role in comprehending and addressing complex skin disorders with immune system involvement. The paper explores the knowledge known so far and the evolution and achievements of AI in diagnosis; discusses segmentation and the classification of medical images; and reviews existing challenges, in immunological-related skin diseases. From our review, the role of AI has emerged, especially in the analysis of images for both diagnostic and severity assessment purposes. Furthermore, the possibility of predicting patients' response to therapies is emerging, in order to create tailored therapies.
PubMed: 38672786
DOI: 10.3390/life14040516 -
Optics Letters Nov 2023We investigate the non-Hermitian Hofstadter-Harper model composed of microring resonators, in which the non-Hermitian skin effect (NHSE) is particularly analyzed. The...
We investigate the non-Hermitian Hofstadter-Harper model composed of microring resonators, in which the non-Hermitian skin effect (NHSE) is particularly analyzed. The effect is achieved through the interaction between well-designed gain-loss layouts and artificial gauge fields. Remarkably, we reveal the emergence of a hybrid skin-topological effect (HSTE), where only the original topological edge modes convert to skin modes while bulk modes remain extended. By changing the distributions of gauge fields, we show the NHSE can manifest itself in bulk modes and be localized at specific edges. Using the equivalence of sites in the bulk or at boundaries to 1D SSH chains, we analyze the potential cancellation of NHSE in these configurations. Additionally, we demonstrate a new, to the best of our knowledge, type of HSTE in topological insulators which emerge at any gain-loss interfaces. The study may improve the understanding of the NHSE behavior in 2D topological systems and provide a promising avenue for tuning light propagation and localization.
PubMed: 37910753
DOI: 10.1364/OL.503244