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.

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.

Betaine combined with traditional Chinese medicine ointment to treat skin wounds in microbially infected diabetic mice

BACKGROUND Skin wounds are highly common in diabetic patients,and with increasing types of pathogenic bacteria and antibiotic resistance,wounds and infections in diabetic patients are difficult to treat and heal.AIM To explore the effects of betaine ointment(BO)in promoting the healing of skin wounds and reducing the inflammation and apoptosis of skin cells in microbially infected diabetic mice.METHODS By detecting the minimum inhibitory concentrations(MICs)of betaine and plant monomer components such as psoralen,we prepared BO with betaine as the main ingredient,blended it with traditional Chinese medicines such as gromwell root and psoralen,and evaluated its antibacterial effects and safety in vitro and in vivo.The skin infection wound models of ordinary mice and diabetic mice were constructed,and the OTC drugs mupirocin ointment and Zicao ointment were used as controls to evaluate the antibacterial effects in vivo and the anti-inflammatory and anti-apoptotic effects of BO.RESULTS The MICs of betaine against microorganisms such as Staphylococcus aureus(S.aureus),Candida albicans and Cryptococcus neoformans ranged from 4 to 32μg/mL.Gromwell root and psoralea,both of which contain antimicrobial components,mixed to prepare BO with MICs ranging from 16 to 64μg/mL,which is 32-256 times lower than those of Zicao ointment,although the MIC is greater than that of betaine.After 15 days of treatment with BO for USA300-infected ordinary mice,the wound scab removal rates were 83.3%,while those of mupirocin ointment and Zicao ointment were 66.7%and 0%,respectively,and the differences were statistically significant.In diabetic mice,the wound scab removal rate of BO and mupirolacin ointment was 80.0%,but BO reduced wound inflammation and the apoptosis of skin cells and facilitated wound healing.CONCLUSION The ointment prepared by mixing betaine and traditional Chinese medicine can effectively inhibit common skin microorganisms and has a strong effect on the skin wounds of sensitive or drug-resistant S.aureus-infected ordinary mice and diabetic mice.

Acellular fish skin grafts in diabetic foot ulcer care:Advances and clinical insights

Diabetic foot ulcers(DFUs)represents a significant public health issue,with a rising global prevalence and severe potential complications including amputation.Traditional treatments often fall short due to various limitations such as high recurrence rates and extensive resource utilization.This editorial explores the innovative use of acellular fish skin grafts as a transformative approach in DFU management.Recent studies and a detailed case report highlight the efficacy of acellular fish skin grafts in accelerating wound closure,reducing dressing changes,and enhancing patient outcomes with a lower socio-economic burden.Despite their promise,challenges such as limited availability,patient acceptance,and the need for further research persist.Addressing these through more extensive randomized controlled trials and fostering a multidisciplinary treatment approach may optimize DFU care and reduce the global health burden associated with these complex wounds.

New skin closure system facilitates wound healing after cardiovascular implantable electronic device surgery

The manuscript describes the efficacy of a new skin closure system(Zip Line?) for wound closure after pacemaker/implantable cardioverter defibrillator surgery. The system is particularly useful when wound healingis difficult with traditional methods and in patients at high risk for surgical site infections(SSIs). This skin closure option is easy and quick to apply and remove, and produces excellent cosmetic results. Although it is associated with a minimal expense upcharge, the benefits, including the potential for decrease in SSI, make it attractive and worth considering for skin closure in device patients, particularly those at increased risk of complications.

Skin-inspired electronics:emerging semiconductor devices and systems

Current electronics are driven by advanced microfabrication for fast and efficient information processing.In spite of high performance,these wafer-based devices are rigid,non-degradable,and unable to autonomous repair.Skin-inspired electronics have emerged as a new class of devices and systems for next-generation flexible and wearable electronics.The technology gains inspiration from the structures,properties,and sensing mechanisms of the skin,which may find a broad range of applications in cutting-edge fields such as healthcare monitoring,human-machine interface,and soft robotics/prostheses.Practical demands have fueled the development of electronic materials with skin-like properties in terms of stretchability,self-healing capability,and biodegradability.These materials provide the basis for functional sensors with innovative and biomimetic designs.Further system-level integrations and optimizations enable new forms of electronics for real-world applications.This review summarizes recent advancements in this active area and speculates on future directions.

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.

Evolution of fracture permeability due to co-colloidal bacterial transport in a coupled fracture-skin-matrix system

A numerical model is developed for investigating the evolution of fracture permeability in a coupled fracture-matrix system in the presence of fracture-skin with simultaneous colloidal and bacte- rial transport, by taking into account the effects of thermal stress and silica precipitation/dissolution, which is computed using linear reaction kinetics. The non-linear coupled equations are numerically modeled using the fully implicit finite difference method and a constant continuous source is adopted while modeling thermal, contaminant, colloidal and bacterial transport. Due to co-colloid bacterial trans- port under non-isothermal conditions, in a coupled fracture-skin-matrix system, the fracture apertures vary spatially, with a corresponding pressure variation for a constant discharge. A series of numerical experiments were conducted for analyzing the spatial variation of fracture aperture in response to the combined effects of thermal stress, silica precipitation/dissolution, and simultaneous colloidal and bacte- rial transport in the presence of the fracture-skin. The simulation results suggest that temperature and contaminant concentration of the mobile fluid within the fracture increases with reduction in initial frac- ture aperture. The pattern of variation followed by the fracture aperture is nearly the same in the presence and absence of bacterial transport but the magnitude of the fracture aperture is low under the influence of bacterial transport. The variation in the fracture aperture resulting from precipitation-dissolution and thermoelastic stress is significant when the fracture aperture is very low and reduces with increment in fracture aperture. The variation in fracture aperture and pressure remains the same for both undersaturated and supersaturated fluid entering the fracture due to the influence of bacterial transport at the inlet of the fracture.

Scalable Skin Lesion Multi-Classification Recognition System

Skin lesion recognition is an important challenge in the medical field.In this paper,we have implemented an intelligent classification system based on convolutional neural network.First of all,this system can classify whether the input image is a dermascopic image with an accuracy of 99%.And then diagnose the dermoscopic image and the non-skin mirror image separately.Due to the limitation of the data,we can only realize the recognition of vitiligo by non-skin mirror.We propose a vitiligo recognition based on the probability average of three structurally identical CNN models.The method is more efficient and robust than the traditional RGB color space-based image recognition method.For the dermoscopic classification model,we were able to classify 7 skin lesions,use weighted optimization to overcome the unbalanced data set,and greatly improve the sensitivity of the model by means of model fusion.The optimization and expansion of the system depend on the increase of database.

Measurement of Electron Return Effect and Skin Dose Reduction by a Bolus in an Anthropomorphic Physical Phantom under a Magnetic Resonance Guided Linear Accelerator (MR-LINAC) System

Background: Magnetic resonance image-guided radiation therapy (MR-IGRT) promises more precise and effective radiation treatments compared to conventional IGRT by using real-time on-board MR imaging. Under the influence of a magnetic field, however, secondary electrons exiting a surface can be forced in a circular path and re-enter the medium, resulting in dose increase at a beam-exit surface, called the electron return effect (ERE). The purpose of the study is to compare the exit skin dose computed by Monte Carlo dose calculation with measurements using an adult anthropomorphic phantom and to measure the effect of skin dose reduction by adding 1 cm-thick bolus. Method: The plan was compared with measurements using an adult anthropomorphic phantom combined with radiochromic films and thermoluminescent dosimeters. We also measured the skin dose reduction by adding 1 cm-thick bolus on the frontal surface of the phantom. Results: We found that 1 cm-thick bolus reduced the skin dose by up to 20% both in measurements and calculations. The plan was found to overestimate the measured skin dose by about 10% and there was no significant difference in the bolus effect between the breast skin and the skin (without breast attachment) doses. Conclusion: In conclusion, we confirmed the ERE effect on the anthropomorphic phantom under the magnetic field and the exit skin dose reduction by adding a bolus. Skin dose measurements using anthropomorphic phantom may be helpful to evaluate more realistic skin dose and the bolus effect in the magnetic field.

Nanozyme‑Engineered Hydrogels for Anti‑Inflammation and Skin Regeneration

Inflammatory skin disorders can cause chronic scarring and functional impairments,posing a significant burden on patients and the healthcare system.Conventional therapies,such as corticosteroids and nonsteroidal anti-inflammatory drugs,are limited in efficacy and associated with adverse effects.Recently,nanozyme(NZ)-based hydrogels have shown great promise in addressing these challenges.NZ-based hydrogels possess unique therapeutic abilities by combining the therapeutic benefits of redox nanomaterials with enzymatic activity and the water-retaining capacity of hydrogels.The multifaceted therapeutic effects of these hydrogels include scavenging reactive oxygen species and other inflammatory mediators modulating immune responses toward a pro-regenerative environment and enhancing regenerative potential by triggering cell migration and differentiation.This review highlights the current state of the art in NZ-engineered hydrogels(NZ@hydrogels)for anti-inflammatory and skin regeneration applications.It also discusses the underlying chemo-mechano-biological mechanisms behind their effectiveness.Additionally,the challenges and future directions in this ground,particularly their clinical translation,are addressed.The insights provided in this review can aid in the design and engineering of novel NZ-based hydrogels,offering new possibilities for targeted and personalized skin-care therapies.

Numerical Estimation of the Thermal Response of Thermal Protective Clothing-Air Gap-Human Skin Micro-system

Thermal protective clothing has been recognized as the primary shielding against emergency fire hazard and inflammable gas leakage. Therefore,the thermal response of human covered with thermal protective clothing under high temperature is the key work to investigate the thermal insulation of thermal protective clothing. A coupling model composed of thermal protective clothing,air gap and human skin is established and the temperature of the micro-system is numerically solved via the finite element method( FEM).Especially,the heat transfer of air gap located between clothing and human skin considering conduction and radiation is established while the human skin layers involve the effect of blood perfusion. Then the effect of thermophysical properties( thermal conductivity and volumetric capacity) of fabric and thickness of fabric and air on the thermal response of the micro-system is elucidated and compared.The results indicate that the volumetric heat capacity of fabric is the key parameter to affect the thermal shielding performance of thermal protective clothing,and the thicker fabric thickness and air gap thickness can improve the thermal protective properties of the micro-system.

Ultraconformable Integrated Wireless Charging Micro-Supercapacitor Skin

Conformable and wire-less charging energy storage devices play important roles in enabling the fast development of wearable,non-contact soft electronics.However,current wire-less charging power sources are still restricted by limited flexural angles and fragile connection of components,resulting in the failure expression of performance and constraining their fur-ther applications in health monitoring wearables and moveable artificial limbs.Herein,we present an ultracompatible skin-like integrated wireless charging micro-supercapacitor,which building blocks(including electrolyte,electrode and substrate)are all evaporated by liquid precursor.Owing to the infiltration and permeation of the liquid,each part of the integrated device attached firmly with each other,forming a compact and all-in-one configuration.In addition,benefitting from the controllable volume of electrode solution precursor,the electrode thickness is easily regulated varying from 11.7 to 112.5μm.This prepared thin IWC-MSC skin can fit well with curving human body,and could be wireless charged to store electricity into high capacitive micro-supercapacitors(11.39 F cm-3)of the integrated device.We believe this work will shed light on the construction of skin-attachable electronics and irregular sensing microrobots.

Cytotoxicity,in Vivo Skin Irritation and Acute Systemic Toxicity of the Mesoporous Magnesium Carbonate Upsalite^(█)

Upsalite®is a mesoporous magnesium carbonate synthesized without using surfactants and therefore highly attractive from environmental and production economy points of view. The material has recently been suggested as drug delivery vehicle and as topical bacteriostatic agent. In order to continue exploring these and other bio-related applications of the material, primary biocompatibility studies are needed. Herein we present the first in vivo acute systemic toxicity and skin irritation analyses as well as in vitro cytotoxicity evaluations of Upsalite®. The material was found to be non-toxic for human dermal fibroblasts cells up to a concentration of 1000 μg/ml and 48 h exposure in contrast to the mesoporous silica material SBA-15, used as reference, which significantly affected cell viability at particle concentration of 500 and 1000 μg/ml after the same exposure time. Topical application of Upsalite®resulted in negligible cutaneous reactions in a rabbit skin irritation model and no evidence of significant systemic toxicity was found when saline extracts of Upsalite®were injected in mice. Injection of sesame oil extract, however, resulted in transient weight loss, most likely due to injection of particles, and not toxic leachables. The presented results form the basis for future development of Upsalite®and similar mesoporous materials in biomedical applications and further toxicity as well as biocompatibility studies should be directed towards specific areas of use.

Multistage Microstructured Ionic Skin for Real-Time Vital Signs Monitoring and Human-Machine Interaction

Skin-like electronics research aiming to mimic even surpass human-like specific tactile cognition by operating perception-to-cognition-to-feedback of stimulus to build intelligent cognition systems for certain imperceptible or inappreciable signals was so attractive.Herein,we constructed an all-in-one tri-modal pressure sensing wearable device to address the issue of power supply by integrating multistage microstructured ionic skin(MM i-skin)and thermoelectric self-power staffs,which exhibits high sensitivity simultaneously.The MM i-skin with multi-stage“interlocked”configurations achieved precise recognition of subtle signals,where the sensitivity reached up to 3.95 kPa^(−1),as well as response time of 46 ms,cyclic stability(over 1500 cycles),a wide detection range of 0–200 kPa.Furthermore,we developed the thermoelectricity nanogenerator,piezoelectricity nanogenerator,and piezocapacitive sensing as an integrated tri-modal pressure sensing,denoted as P-iskin,T-iskin,and C-iskin,respectively.This multifunctional ionic skin enables real-time monitoring of weak body signals,rehab guidance,and robotic motion recognition,demonstrating potential for Internet of things(IoT)applications involving the artificial intelligence-motivated sapiential healthcare Internet(SHI)and widely distributed human-machine interaction(HMI).

A Polyvinyl Alcohol/Acrylamide Hydrogel with Enhanced Mechanical Properties Promotes Full-Thickness Skin Defect Healing by Regulating Immunomodulation and Angiogenesis Through Paracrine Secretion

Hydrogel-based tissue-engineered skin has attracted increased attention due to its potential to restore the structural integrity and functionality of skin.However,the mechanical properties of hydrogel scaffolds and natural skin are substantially different.Here,we developed a polyvinyl alcohol(PVA)/acrylamide based interpenetrating network(IPN)hydrogel that was surface modified with polydopamine(PDA)and termed Dopa-gel.The Dopa-gel exhibited mechanical properties similar to native skin tissue and a superior ability to modulate paracrine functions.Furthermore,a tough scaffold with tensile resistance was fabricated using this hydrogel by three-dimensional printing.The results showed that the interpenetration of PVA,alginate,and polyacrylamide networks notably enhanced the mechanical properties of the hydrogel.Surface modification with PDA endowed the hydrogels with increased secretion of immunomodulatory and proangiogenic factors.In an in vivo model,Dopa-gel treatment accelerated wound closure,increased vascularization,and promoted a shift in macrophages from a proinflammatory M1 phenotype to a prohealing and anti-inflammatory M2 phenotype within the wound area.Mechanistically,the focal adhesion kinase(FAK)/extracellular signal-related kinase(ERK)signaling pathway may mediate the promotion of skin defect healing by increasing paracrine secretion via the Dopa-gel.Additionally,proangiogenic factors can be induced through Rho-associated kinase-2(ROCK-2)/vascular endothelial growth factor(VEGF)-mediated paracrine secretion under tensile stress conditions.Taken together,these findings suggest that the multifunctional Dopa-gel,which has good mechanical properties similar to those of native skin tissue and enhanced immunomodulatory and angiogenic properties,is a promising scaffold for skin tissue regeneration.

Skin lesion classification system using a Knearest neighbor algorithm

One of the most critical steps in medical health is the proper diagnosis of the disease.Dermatology is one of the most volatile and challenging fields in terms of diagnosis.Dermatologists often require further testing,review of the patient’s history,and other data to ensure a proper diagnosis.Therefore,finding a method that can guarantee a proper trusted diagnosis quickly is essential.Several approaches have been developed over the years to facilitate the diagnosis based on machine learning.However,the developed systems lack certain properties,such as high accuracy.This study proposes a system developed in MATLAB that can identify skin lesions and classify them as normal or benign.The classification process is effectuated by implementing the K-nearest neighbor(KNN)approach to differentiate between normal skin and malignant skin lesions that imply pathology.KNN is used because it is time efficient and promises highly accurate results.The accuracy of the system reached 98%in classifying skin lesions.

Skin Melanoma Classification System Using Deep Learning

The deadliest type of skin cancer is malignant melanoma.The diagnosis requires at the earliest to reduce the mortality rate.In this study,an efficient Skin Melanoma Classification(SMC)system is presented using dermoscopic images as a non-invasive procedure.The SMC system consists of four modules;segmentation,feature extraction,feature reduction and finally classification.In the first module,k-means clustering is applied to cluster the colour information of dermoscopic images.The second module extracts meaningful and useful descriptors based on the statistics of local property,parameters of Generalized Autoregressive Conditional Heteroscedasticity(GARCH)model of wavelet and spatial patterns by Dominant Rotated Local Binary Pattern(DRLBP).The third module reduces the features by the t-test,and the last module uses deep learning for the classification.The individual performance shows that GARCH parameters of 3rd DWT level sub-bands provide 92.50%accuracy than local properties(77.5%)and DRLBP(88%)based features for the 1st stage(normal/abnormal).For the 2nd stage(benign/malignant),it is 95.83%(GRACH),90%(DRLBP)and 80.8%(Local Properties).The selected 2%of features from the combination gives 99.5%and 100%for 1st and 2nd stage of the SMC system.The greatest degree of success is achieved on PH2 database images using two stages of deep learning.It can be used as a pre-screening tool as it provides 100%accuracy for melanoma cases.

The Effects of Green Kiwifruit Ingestion on Digestive Health, Blood Flow, Skin Health, and the Autonomic Nervous System

We aimed to assess the impact of consuming two Zespri Hayward green kiwifruit a day on 11 healthy women subjects over a period of 4 consecutive weeks. We analyzed the effects of kiwifruit consumption on intestinal, abdominal, and bowel movement related discomfort, bowel movement frequency, peripheral blood flow, skin health, and autonomic nervous system activity. This study was a randomized control trial, consisting of a four-week intervention period. Participants were divided to ensure equal age distributions and then randomly placed into two intervention groups: a kiwifruit consumption group (n = 11) and a control group (no kiwifruit consumption) (n = 5). The kiwifruit consumption group was instructed to consume two kiwifruit a day during the 4-week intervention period, while subjects in the control group were instructed not to consume kiwifruit for the duration of the study. Besides a restriction from eating yogurt and other fruits, subjects were requested to eat their meals as per usual. The results of this study showed a significant decrease in intestinal, abdominal, and bowel movement discomfort, and a significant increase in bowel movement frequency, at 4 weeks of kiwifruit consumption compared to before consumption. In addition, subjects in the kiwifruit consumption group experienced a significant increase in blood flow, particularly in the index and middle finger at 2 and 4 weeks of kiwifruit consumption. Furthermore, subjects in the kiwifruit consumption group experienced a significant increase in skin brightness at 4 weeks of kiwifruit consumption compared to before consumption. The results of this study suggest that kiwifruit appears to be a delicious and safe option for intestinal, abdominal, and bowel movement discomfort interventions for healthy women. In addition, kiwifruit may aid in increasing bowel movement frequency, peripheral blood flow, and brightness of skin among healthy women as well.

Skin Lesion Classification System Using Shearlets

The main cause of skin cancer is the ultraviolet radiation of the sun.It spreads quickly to other body parts.Thus,early diagnosis is required to decrease the mortality rate due to skin cancer.In this study,an automatic system for Skin Lesion Classification(SLC)using Non-Subsampled Shearlet Transform(NSST)based energy features and Support Vector Machine(SVM)classifier is proposed.Atfirst,the NSST is used for the decomposition of input skin lesion images with different directions like 2,4,8 and 16.From the NSST’s sub-bands,energy fea-tures are extracted and stored in the feature database for training.SVM classifier is used for the classification of skin lesion images.The dermoscopic skin images are obtained from PH^(2) database which comprises of 200 dermoscopic color images with melanocytic lesions.The performances of the SLC system are evaluated using the confusion matrix and Receiver Operating Characteristic(ROC)curves.The SLC system achieves 96%classification accuracy using NSST’s energy fea-tures obtained from 3^(rd) level with 8-directions.