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Intelligent Dermatologist Tool for Classifying Multiple Skin Cancer Subtypes by Incorporating Manifold Radiomics Features Categories.

ABSTRACT: The rates of skin cancer (SC) are rising every year and becoming a critical health issue worldwide. SC's early and accurate diagnosis is the key procedure to reduce these rates and improve survivability. However, the manual diagnosis is exhausting, complicated, expensive, prone to diagnostic error, and highly dependent on the dermatologist's experience and abilities. Thus, there is a vital need to create automated dermatologist tools that are capable of accurately classifying SC subclasses. Recently, artificial intelligence (AI) techniques including machine learning (ML) and deep learning (DL) have verified the success of computer-assisted dermatologist tools in the automatic diagnosis and detection of SC diseases. Previous AI-based dermatologist tools are based on features which are either high-level features based on DL methods or low-level features based on handcrafted operations. Most of them were constructed for binary classification of SC. This study proposes an intelligent dermatologist tool to accurately diagnose multiple skin lesions automatically. This tool incorporates manifold radiomics features categories involving high-level features such as ResNet-50, DenseNet-201, and DarkNet-53 and low-level features including discrete wavelet transform (DWT) and local binary pattern (LBP). The results of the proposed intelligent tool prove that merging manifold features of different categories has a high influence on the classification accuracy. Moreover, these results are superior to those obtained by other related AI-based dermatologist tools. Therefore, the proposed intelligent tool can be used by dermatologists to help them in the accurate diagnosis of the SC subcategory. It can also overcome manual diagnosis limitations, reduce the rates of infection, and enhance survival rates.

SUBMITTER: Attallah O

PROVIDER: S-EPMC8457955 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMolecularly targeted therapies, such as monoclonal antibodies (mAbs) and Janus Kinase inhibitors (JAKis), have emerged as essential tools in the treatment of dermatological diseases. These therapies modulate the immune system through specific signaling pathways, providing effective alternatives to traditional systemic immunosuppressive agents. This review aims to provide an updated summary of targeted immune therapies for inflammatory skin diseases, considering their pathophysiology, efficacy, dosage, and safety profiles.MethodsThe review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. A systematic search was conducted on PubMed over the past 10 years, focusing on randomized clinical trials, case reports, and case series related to targeted immune therapies in dermatology. Eligibility criteria were applied, and data were extracted from each study, including citation data, study design, and results.ResultsWe identified 1360 non-duplicate articles with the initial search strategy. Title and abstract review excluded 1150, while a full-text review excluded an additional 50 articles. The review included 143 studies published between 2012 and 2022, highlighting 39 drugs currently under investigation or in use for managing inflammatory skin diseases.Study limitationsThe heterogeneity of summarized information limits this review. Some recommendations originated from data from clinical trials, while others relied on retrospective analyses and small case series. Recommendations will likely be updated as new results emerge.ConclusionTargeted therapies have revolutionized the treatment of chronic skin diseases, offering new options for patients unresponsive to standard treatments. Paradoxical reactions are rarely observed. Further studies are needed to fully understand the mechanisms and nature of these therapies. Overall, targeted immune therapies in dermatology represent a promising development, significantly improving the quality of life for patients with chronic inflammatory skin diseases.

Project description:ImportanceSeveral studies have linked chronic inflammatory skin diseases (CISDs) with venous thromboembolism (VTE) in a range of data sources with mixed conclusions.ObjectiveTo examine the incidence of VTE in patients with vs without CISD.Design, setting, and participantsA cohort study using commercial insurance claims data from a nationwide US health care database from January 1, 2004, through 2019 was conducted. A total of 158 123 patients with dermatologist-recorded psoriasis, atopic dermatitis, alopecia areata, vitiligo, or hidradenitis suppurativa were included. Risk-set sampling identified patients without a CISD. Patient follow-up lasted until the first of the following occurred: VTE, death, disenrollment, or end of data stream.ExposuresPatients with vs without CISD.Main outcomes and measuresVenous thromboembolism events were identified with validated algorithms. Incidence rates were computed before and after 1:1 propensity-score matching to account for VTE risk factors. Hazard ratios were estimated to compare the incidence of VTE in the CISD vs non-CISD cohorts.ResultsA total of 158 123 patients were identified with CISD: with psoriasis (n = 96 138), atopic dermatitis (n = 30 418), alopecia areata (n = 17 889), vitiligo (n = 7735), or HS (n = 5934); 9 patients had 2 of these conditions. A total of 1 570 387 patients were without a CISD. The median follow-up time was 1.9 years (interquartile range, 0.8-4.0 years) in patients with CISD. The incidence rate (per 1000 person-years) of outpatient or inpatient VTE was 1.57 in psoriasis, 1.83 in atopic dermatitis, 0.94 in alopecia areata, 0.93 in vitiligo, 1.65 in HS and 1.53 in CISD overall, compared with 1.76 in patients without a CISD. Incidence rates increased in patients aged 50 years or older (2.3 per 1000 person-years) and decreased in those aged 18 to 49 years (0.8 per 1000 person-years). After propensity-score matching to patients without a CISD, the hazard ratio (HR) of VTE was 0.86 (95% CI, 0.75-0.99) in psoriasis, 1.19 (95% CI, 0.95-1.48) in atopic dermatitis, 0.97 (95% CI, 0.65-1.46) in alopecia areata, 0.90 (95% CI, 0.49-1.65) in vitiligo, 1.64 (95% CI, 0.82-3.27) in hidradenitis suppurativa, and 0.94 (95% CI, 0.84-1.05) in CISD overall.Conclusions and relevanceIn this large-scale cohort study, CISDs were not associated with an increased incidence of VTE after controlling for relevant VTE risk factors in a representative dermatology patient population.

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Intelligent Dermatologist Tool for Classifying Multiple Skin Cancer Subtypes by Incorporating Manifold Radiomics Features Categories.

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