A Comprehensive Systematic Review: Advancements in Skin Cancer Classification and Segmentation Using the ISIC Dataset

The International Skin Imaging Collaboration(ISIC)datasets are pivotal resources for researchers in machine learning for medical image analysis,especially in skin cancer detection.These datasets contain tens of thousands of dermoscopic photographs,each accompanied by gold-standard lesion diagnosis metadata.Annual challenges associated with ISIC datasets have spurred significant advancements,with research papers reporting metrics surpassing those of human experts.Skin cancers are categorized into melanoma and non-melanoma types,with melanoma posing a greater threat due to its rapid potential for metastasis if left untreated.This paper aims to address challenges in skin cancer detection via visual inspection and manual examination of skin lesion images,processes historically known for their laboriousness.Despite notable advancements in machine learning and deep learning models,persistent challenges remain,largely due to the intricate nature of skin lesion images.We review research on convolutional neural networks(CNNs)in skin cancer classification and segmentation,identifying issues like data duplication and augmentation problems.We explore the efficacy of Vision Transformers(ViTs)in overcoming these challenges within ISIC dataset processing.ViTs leverage their capabilities to capture both global and local relationships within images,reducing data duplication and enhancing model generalization.Additionally,ViTs alleviate augmentation issues by effectively leveraging original data.Through a thorough examination of ViT-based methodologies,we illustrate their pivotal role in enhancing ISIC image classification and segmentation.This study offers valuable insights for researchers and practitioners looking to utilize ViTs for improved analysis of dermatological images.Furthermore,this paper emphasizes the crucial role of mathematical and computational modeling processes in advancing skin cancer detection methodologies,highlighting their significance in improving algorithmic performance and interpretability.

Enhancing Skin Cancer Diagnosis with Deep Learning:A Hybrid CNN-RNN Approach

Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and Recurrent Neural Network (CNN-RNN) model with a ResNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research.

The Value of Excipients and the Required Understanding of the Biological System in Product Development: An Impactful Example of Curaderm, a Topical Skin Cancer Treatment

The incidences of nonmelanoma skin cancer are increasing worldwide, and the ongoing war on its treatment necessitates the development of effective and non-invasive methods. Through basic and clinical research, non-invasive treatments like Curaderm have been developed, leading to improved quality of life for patients. Excipients, previously considered inactive ingredients, play a crucial role in enhancing the performance of topical formulations. The development of Curaderm emphasizes the importance of understanding the interactions between active ingredients, excipients, and the biological system to create effective and affordable pharmaceutical formulations. The systematic approach taken in the development of Curaderm, starting from the observation of the anticancer activity of natural solasodine glycosides and progressing through toxicological and efficacy studies in cell culture, animals, and humans, has provided insights into the pharmacokinetics and pharmacodynamics of solasodine glycosides. It is crucial to determine these pharmacological parameters within the skin’s biological system for maximal effectiveness and cost-effectiveness of a skin cancer treatment. Curaderm, as a topical treatment for nonmelanoma skin cancer, offers benefits beyond those obtained from other topical treatments, providing hope for improved quality of life for patients.

Unique Clinical Features of Curaderm when Treating Skin Cancers

Basal cell carcinoma is the most common form of skin cancer and the most frequently occurring form of all cancers. Conventional treatments to remove or destroy basal cell carcinoma are indiscriminate and also remove or destroy normal skin cells resulting in compromised cosmetic outcomes. Consequences of these treatments include body-image issues, anxiety, post-traumatic stress disorder, depression, and poorer quality of social and family life. A progressive topical cream formulation, Curaderm, containing the natural BEC glycoalkaloids, have shown to have advantages over conventional treatments. However, comprehensive clinical features of the skin cancer lesions during treatment with Curaderm have to date not been reported. This report shows that using unpublished data from a large number of patients with varying sizes, types and locations of basal cell carcinomas when treated with Curaderm in a phase 3 trial, an initial increase in size of the lesions occur, followed by a reverse course, leading to complete removal of the skin cancer. The specificity and mode of action of Curaderm explains the superior cosmetic outcomes when compared with conventional therapies.

Gold Standard for Skin Cancer Treatment: Surgery (Mohs) or Microscopic Molecular-Cellular Therapy (Curaderm)?

Non-melanoma skin cancers or keratinocyte cancers such as basal cell carcinoma and squamous cell carcinoma make up approximately 80% and 20% respectively, of skin cancers with the 6 million people that are treated annually in the United States. 1 in 5 Americans and 2 in 3 Australians develop skin cancer by the age of 70 years and in Australia it is the most expensive, amassing $1.5 billion, to treat cancers. Non-melanoma skin cancers are often self-detected and are usually removed by various means in doctors’ surgeries. Mohs micrographic surgery is acclaimed to be the gold standard for the treatment of skin cancer. However, a novel microscopic molecular-cellular non-invasive topical therapy described in this article, challenges the status of Mohs procedure for being the acclaimed gold standard.

Induction of apoptosis by arsenic trioxide and hydroxycamptothecin in gastric cancer cells in vitro

AIM To study the effects of arsenic trioxide andHCPT on different degrees of differentiated gastriccancer cells（SGC-7901,MKN-45,MKN-28）withrespect to both cytotoxicity and induction ofapoptosis in vitro.METHODS The cytotoxicity of As2O3 and HCPTon gastric cancer cells was determined by MTTassay.Morphologic changes of apoptosis ofgastric cancer cells were observed by lightmicroscopy and transmission electron microscopy.Apoptosis and cell cycle changes of gastric cancercells induced by HCPT and As2O3 were investigatedby TUNEL method and flow cytometry.RESULTS As2O3 and HCPT had remarkablecytotoxic effects on different degrees ofdifferentiated gastric cancer cells.The IC50ofAs2O3 on well differentiated gastric cancer cellMKN-28,moderately differentiated gastric cancercell SGC-7901,and poorly differentiated gastriccancer cell MKN-28 were 8.91 μmol/L,10.57μmol/L,and 11.65 μmol/L,respectively.The IC50of HCPT on MKN-28,SGC-7901,and MKN-45 were9.35 mg/L,10.21 mg/L,and 12.63 mg/Lrespectively after 48 h treatment.After 12 h ofexposure to both drugs,gastric cancer cellsexhibited morphologic features of apoptosis,including cell shrinkage,nuclear condensation, and formation of apoptotic bodies.A typicalsubdiploid peak before G0/G1 phase was observedby flow cytometry.The apoptotic rates of SGC-7901,MKN-45,and MKN-28 were 13.84%,22.52%,and 9.68%,respectively after 48 hexposure to 10 μmol/L As2O3.The apoptotic ratesof SGC-7901,MKN-45,and MKN-28 were 21.88%,12.35%,and 30.26%,respectively after 48 hexposure to 10 mg/L HCPT.The apoptotic indicewere 7%-15% as assessed by TUNEL method.The effect of As2O3 on SGC-7901 showedremarkable cell cycle specificity,which inducedcell death in G1 phase,and blocked G2/M phase.HCPT also showed a remarkable cell cyclespecificity,by inducing cell death and apoptosis inG1 phase and arrest of proliferation at S phase.CONCLUSION As2O3 and HCPT exhibitsignificant cytotoxicity on gastric cancer cells byinduction of apoptosis.As2O3 and HCPT mighthave a promising prospect in the treatment ofgastric cancer,which needs to be further studied.

Recent advances in arsenic trioxide encapsulated nanoparticles as drug delivery agents to solid cancers

Since arsenic trioxide was first approved as the front line therapy for acute promyelocytic leukemia 25 years ago,its anti-cancer properties for various malignancies have been under intense investigation.However,the clinical successes of arsenic trioxide in treating hematological cancers have not been translated to solid cancers.This is due to arsenic＇s rapid clearance by the body＇s immune system before reaching the tumor site.Several attempts have henceforth been made to increase its bioavailability toward solid cancers without increasing its dosage albeit without much success.This review summarizes the past and current utilization of arsenic trioxide in the medical field with primary focus on the implementation of nanotechnology for arsenic trioxide delivery to solid cancer cells.Different approaches that have been employed to increase arsenic＇s efficacy,specificity and bioavailability to solid cancer cells were evaluated and compared.The potential of combining different approaches or tailoring delivery vehicles to target specific types of solid cancers according to individual cancer characteristics and arsenic chemistry is proposed and discussed.

Arsenic trioxide induces apoptosis of human gastrointestinal cancer cells

AIM: To investigate the changes in apoptosis in gastrointestinal cancer cells from patients with gastrointestinal cancers treated with arsenic trioxide (As2O3); and to study the possible molecular mechanisms of such changes by detecting the expression levels of p53 and Bcl-2.

A study on arsenic trioxide inducing in vitro apoptosis of gastric cancer cell lines

INTRODUCTION Cell apoptosis,which involves the biologic regulation of the numbers and vital activity of cells,is an important metaboloc process in both normal cells and tumor cells.

Anti-hepatoma effect of arsenic trioxide on experimental liver cancer induced by 2-acetamidofluorene in rats

AIM： To study the anti-hepatoma efficiency of arsenic trioxide （As2O3） in the treatment of experimental rat hepatocellular carcinoma （HCC） induced by 2-acetamidofluorene （2-FAA） and to elucidate the possible mechanisms. METHODS： SD rats （2 mo old） had been fed with 2-FAA for 8 wk to induce HCC, and then they were treated with As2O3 or matrine. On d 29, the rats were killed and the liver was weighed and liver tumors were counted. The histological changes of liver tissue were observed under microscope, and the cellular dynamic parameters were studied by flow cytometry. Immunohistochemistry （two-step method） was used to observe the expression of vascular endothelial growth factor （VEGF） and micro-vessel density （MVD） on consecutive sections. The pathological parameters were also analyzed, the levels of serum aspartate aminotransferase （AST）, alanine aminotransferase （ALT）, total bilirubin （TBi）, and direct bilirubin （DBi）. RESULTS： The number of liver tumors decreased significantly in groups treated with As2O3, especially in medium-dose （1 mg/kg） group （t = 2.80, P〈0.01）. As2O3 caused HCC cell death via apoptosis; necrosis was seen and apoptosis was common when the dose was 1 mg/kg. Proliferation index decreased sharply in medium-dose （1 mg/kg） group （7.87±4.11 vs24.46±6.49, t= 2087, P〈0.01）, but not in 0.2 mg/kg group. However, S-phase fraction decreased dramatically in both groups, it reached the bottom level only when the dose was i mg/kg compared with control （0.40±0.13 vs3.01±0.51, t= 2.97, P〈0.01）, and it was obviously accompanied with accumulation of cells in G0/G1 （G0/G1 restriction）. The expressions of VEGF and MVD in medium-dose （1 mg/kg） group were significantly lower than normal saline group （0.63±0.74 vs2.44±0.88, P〈0.05; 15.75±3.99 vs47.44±13.41, t= 2.80, P〈0.01）. Compared with normal saline group, mediumand low-dose groups As203 and matrine lowered the levels of ALT in serum （61.46±9.46, 63.75±20.40, 61.18±13.00 vs 108.98±29.86, t= 2.14, P〈0.05）, but had no effect onthe level of serum AST, TBi, and DBi. CONCLUSION： As203 had inhibitory effect on growth of experimental HCC in rats induced by 2-FAA, but had no obvious effect on normal hepatic cells. The mechanisms may involve decrease of cell division, accumulation of cells in G0/G1 phase, apoptosis of tumor cells, and inhibitory effect on angiogenesis through blocking VEGF.

Synergistic effect of all-trans-ret inoic acid and arsenic trioxide on growth inhibition and apoptosis in human hepatoma, breast cancer, and lung cancer cells in vitro

AIM： To investigate the effect of all-trans-retinoic acid （ATRA） on arsenic trioxide （As2O3）-induced apoptosis of human hepatoma, breast cancer, and lung cancer cells in an attempt to find a better combination therapy for solid tumors. METHODS： Human hepatoma cell lines HepG2, Hep3B, human breast cancer cell line MCF-7, and human lung adenocarcinoma cell line AGZY-83-a were treated with As203 together with ATRA. Cell survival fraction was determined by MTT assay, cell viability and apoptosis were measured by annexin V-fluorescein isothiocyanate （FITC） and PI staining, and intracellular glutathione （GSH） and glutathione-S-transferase （GST） activities were determined using commercial kits. RESULTS： Cytotoxicity of ATRA was low. ATRA （0.1, 1, and 10 μmol/L） could synergistically potentiate As2O3 to exert a dose-dependent inhibition of growth and to induce apoptosis in each of the cell lines. HepG2 and Hep3B with low intracellular GSH or GST activities were remarkably sensitive to As2O3 or As2O3＋ATRA, while AGZY-83-a with higher GSH or GST activities was less sensitive to As2O3 or As2O3＋ATRA. Treatment with 2 μmol/L As2O3 for 72 h significantly decreased intracellular GSH and GST levels in each of the cell lines, and 1 μmol/L ATRA alone reduced minimal intracellular GSH and GST levels. ATRA potentiated the effect of As2O3 on intracellular GSH levels, but intracellular GST levels were not significantly affected by the combination of As2O3 and ATRA for 72 h as compared to As2O3 alone.CONCLUSION： ATRA can strongly potentiate As2O3- induced growth-inhibition and apoptosis in each of the cell lines, and two drugs can produce a significant synergic effect. The sensitivity to As2O3 or As2O3＋ATRA is inversely proportional to intracellular GSH or GST levels in each of the cell lines. The GSH redox system may be the possible mechanism by which ATRA synergistically potentiates As203 to exert a dose-dependent inhibition of growth and to induce apoptosis. 2005 The WJG Press and Elsevier Inc. All rights reserved.

Preliminary Study of the in vitro Growth Inhibition of Human Bladder Cancer Cell Line BIU-87 by Arsenic Trioxide

To study the effects of arsenic trioxide (As2O3) on the in vitro growth of human bladder cancer cells and the mechanisms. The growth inhibition rates of human bladder cancer cell line BIU87 by various concentrations of As2O3 were detected by using MTT method. Cell apoptosis was detected by in situ terminally labeled transferase technique and bcl-2 gene expression of BIU-87 cells was observed by SABC immunohistochemical method. The results showed that As2O3 could inhibit the growth of BIU-87 effectively in a dose-dependent manner. After drug's action, the apoptotic bladder cancer cells were obviously increased, which depended on the prolongation of the action time and Bcl-2 expression of BIU-87 cells was decreased significantly. It was suggested that As2O3 could significantly inhibit the growth of bladder human cancer cells. Inducing cell apoptosis by down- regulating the expression of hcl-2 gene might be one of its action mechanisms.

Bladder Cancer and Arsenic Exposure: Differences in the Two Populations Enrolled in A Study in Southwest Taiwan

Objective Analyses of bladder cancer mortality in the Black Foot Disease (BFD) endemic area of southwest Taiwan conducted by Morales et al. showed a discontinuity in risk at 400μg/L arsenic in the drinking water in a stratified analysis and no discontinuity in a continuous analysis. As the continuous analysis presentation had been used by both the NRC and the EPA to assess the carcinogenic risk from arsenic ingestion, an explanation of the discontinuity was sought. Methods Review of 40 years of published health studies of the BFD-endemic area of SW Taiwan showed that earlier publications had limited their cancer associations with arsenic levels in artesian well waters and that the reports of Morales et al., NRC, and EPA failed to do so. Underlying data for the Morales et al. study were obtained from the appendix to the NRC report. Bladder cancer mortality rates were calculated from case counts and person-years of observation for each study village. Villages were categorized by water source according to the descriptions from the underlying study. Graphic and regression analyses were conducted of the bladder cancer mortality rates using exposure as a continuous variable and simultaneously stratifying by water source. Results The median village well arsenic levels ranged from 350 to 934μg/L for villages solely dependent on artesian well water and from 10 to 717μg/L for villages not solely dependent on artesian well water. Bladder cancer mortality rates were found to be dependent upon the arsenic level only for those villages that were solely dependent on artesian well water for their water source. Bladder cancer mortality rates were found to be independent of arsenic level for villages with non-artesian well water sources. Conclusions The data indicate that arsenic exposure levels do not explain the bladder cancer mortality risk in SW Taiwan among villages not dependent upon artesian well water. The association for villages dependent upon artesian well water may be explained either by arsenic acting as a high-dose carcinogen or in artesian well water as a co-carcinogen with some other aspect of artesian well water (possibly humic acid). Arsenic exposure level alone appears to be an insufficient exposure measure to describe the risk of bladder cancer mortality in the BFD-endemic area. Risk analyses that fail to take water source into account are likely to misrepresent the risk characterization, particularly at low arsenic levels.

Mechanisms and Immune Dysregulation in Arsenic Skin Carcinogenesis

Long-term exposure to arsenic is associated with cancers of lung, urinary bladder, kidney, liver and skin. Arsenic car-cinogenesis might result from oxidative stress, altered growth factors, chromosomal abnormality, immune dysregula-tion, and aberrant epigenetic regulations. Bowen’s disease (As-BD) is the most common form of arsenic-induces skin cancers and is characterized by chronicity, multiplicity, and predisposition in sun-spare skin. However, only about 1% of the population exposed to arsenic developped skin cancers, indicating the host immune response plays an important modulatory role in skin carcinogenesis. In this review, we review the pathomechanisms of arsenic skin carcinogenesis and the immune interactions. Arsenic affects innate and adaptive immune responses through CD4+ T cells, monocytes, macrophages, and Langerhans cells. In skin of As-BD, CD4+ T cells undergo selective and differential apoptosis via Fas-FasL interaction. Numbers and dendrites of Langerhans cells are reduced in As-BD lesions. There is a defective homeostasis and aberrant trafficking of Langerhans cells. Such information is essential to understand the molecular mechanism for arsenic carcinogenesis in both skin and in internal organs.

Computer Decision Support System for Skin Cancer Localization and Classification

In this work,we propose a new,fully automated system for multiclass skin lesion localization and classification using deep learning.The main challenge is to address the problem of imbalanced data classes,found in HAM10000,ISBI2018,and ISBI2019 datasets.Initially,we consider a pretrained deep neural network model,DarkeNet19,and fine-tune the parameters of third convolutional layer to generate the image gradients.All the visualized images are fused using a High-Frequency approach along with Multilayered Feed-Forward Neural Network(HFaFFNN).The resultant image is further enhanced by employing a log-opening based activation function to generate a localized binary image.Later,two pre-trained deep models,Darknet-53 and NasNet-mobile,are employed and fine-tuned according to the selected datasets.The concept of transfer learning is later explored to train both models,where the input feed is the generated localized lesion images.In the subsequent step,the extracted features are fused using parallel max entropy correlation(PMEC)technique.To avoid the problem of overfitting and to select the most discriminant feature information,we implement a hybrid optimization algorithm called entropy-kurtosis controlled whale optimization(EKWO)algorithm.The selected features are finally passed to the softmax classifier for the final classification.Three datasets are used for the experimental process,such as HAM10000,ISBI2018,and ISBI2019 to achieve an accuracy of 95.8%,97.1%,and 85.35%,respectively.

Intelligent Multiclass Skin Cancer Detection Using Convolution Neural Networks

The worldwide mortality rate due to cancer is second only to cardiovascular diseases.The discovery of image processing,latest artificial intelligence techniques,and upcoming algorithms can be used to effectively diagnose and prognose cancer faster and reduce the mortality rate.Efficiently applying these latest techniques has increased the survival chances during recent years.The research community is making significant continuous progress in developing automated tools to assist dermatologists in decision making.The datasets used for the experimentation and analysis are ISBI 2016,ISBI 2017,and HAM 10000.In this work pertained models are used to extract the efficient feature.The pertained models applied are ResNet,InceptionV3,and classical feature extraction techniques.Before that,efficient preprocessing is conducted on dermoscopic images by applying various data augmentation techniques.Further,for classification,convolution neural networks were implemented.To classify dermoscopic images on HAM 1000 Dataset,the maximum attained accuracy is 89.30%for the proposed technique.The other parameters for measuring the performance attained 87.34%(Sen),86.33%(Pre),88.44%(F1-S),and 11.30%false-negative rate(FNR).The class with the highest TP rate is 97.6%for Melanoma;whereas,the lowest TP rate was for the Dermatofibroma class.For dataset ISBI2016,the accuracy achieved is 97.0%with the proposed classifier,whereas the other parameters for validation are 96.12%(Sen),97.01%(Pre),96.3%(F1-S),and further 3.7%(FNR).For the experiment with the ISBI2017 dataset,Sen,Pre,F1-S,and FNR were 93.9%,94.9%,93.9%,and 5.2%,respectively.

Diabetes and skin cancers: Risk factors, molecular mechanisms and impact on prognosis

Diabetes and skin cancers have emerged as threats to public health worldwide.However,their association has been less intensively studied.In this narrative review,we explore the common risk factors,molecular mechanisms,and prognosis of the association between cutaneous malignancies and diabetes.Hyperglycemia,oxidative stress,low-grade chronic inflammation,genetic,lifestyle,and environmental factors partially explain the crosstalk between skin cancers and this metabolic disorder.In addition,diabetes and its related complications may interfere with the appropriate management of cutaneous malignancies.Antidiabetic medication seems to exert an antineoplastic effect,however,future large,observation studies with a prospective design are needed to clarify its impact on the risk of malignancy in diabetes.Screening for diabetes in skin cancers,as well as close follow-up for the development of cutaneous malignancies in subjects suffering from diabetes,is warranted.

Fluorescence lifetime imaging microscopy and its applications in skin cancer diagnosis

Fluorescence lifetime(FLT)of fluorophores is sensitive to the changes in their surrounding microenvironment,and hence it can quantitatively reveal the physiological characterization of the tissue under investigation.Fluorescence lifetime imaging microscopy(FLIM)provides not only morphological but also functional information of the tisse by producing spatially resolved image of fuorophore lifetime,which can be used as a signature of disorder and/or malignancy in diseased tissues.In this paper,we begin by introducing the basic principle and common detection methods of FLIM.Then the recent advances in the FLIM-based diagnosis of three different skin cancers,including basal cell carcinoma(BCC),squamous cell carcinoma(SCC)and malignant melanoma(MM)are reviewed.Furthermore,the potential advantages of FLIM in skin cancer diagnosis and the challenges that may be faced in the future are prospected.

Skin Cancer Treatment by Nanoskin Cellulose: Future Cancer Wound Healing

Cancer cells can be proliferating in a few months and years. It depends on cancer stage. Chemotherapy, immunotherapy and anti-metabolic drugs have been used in order to kill cancer cells and prevent immune system weakly and metastasis. However, such drugs can damage healthy cells too. Natural ways to cancer treatments may help whole body to cancer cells. In this work, it was taking off cancer nodule to skin cancer by surgery and we treat the nodule as wound, using Nanoskin® advance cell therapy (ACT), natural extra cellular matrix which releases nutrients to the skin cancer. Our result shows that the cancer nodule disappears in few weeks in skin, because of natural membrane treatment. In addition, we obtained complete wound healing due anticancer nutrients (beta-glucan) delivery to skin.

Smart MobiNet:A Deep Learning Approach for Accurate Skin Cancer Diagnosis

The early detection of skin cancer,particularly melanoma,presents a substantial risk to human health.This study aims to examine the necessity of implementing efficient early detection systems through the utilization of deep learning techniques.Nevertheless,the existing methods exhibit certain constraints in terms of accessibility,diagnostic precision,data availability,and scalability.To address these obstacles,we put out a lightweight model known as Smart MobiNet,which is derived from MobileNet and incorporates additional distinctive attributes.The model utilizes a multi-scale feature extraction methodology by using various convolutional layers.The ISIC 2019 dataset,sourced from the International Skin Imaging Collaboration,is employed in this study.Traditional data augmentation approaches are implemented to address the issue of model overfitting.In this study,we conduct experiments to evaluate and compare the performance of three different models,namely CNN,MobileNet,and Smart MobiNet,in the task of skin cancer detection.The findings of our study indicate that the proposed model outperforms other architectures,achieving an accuracy of 0.89.Furthermore,the model exhibits balanced precision,sensitivity,and F1 scores,all measuring at 0.90.This model serves as a vital instrument that assists clinicians efficiently and precisely detecting skin cancer.