First-time office visit for suspicious skin lesion evaluation as a predictor of high-risk melanoma DOI
Rose Parisi, Hemali Shah, Emily Everdell

et al.

Melanoma Research, Journal Year: 2023, Volume and Issue: 33(6), P. 555 - 556

Published: Oct. 25, 2023

Parisi, Rose; Shah, Hemali; Everdell, Emily; Feustel, Paul; Davis, Lindy Author Information

Language: Английский

Screening for Skin Cancer DOI Open Access
Carol M. Mangione, Michael J. Barry, Wanda K. Nicholson

et al.

JAMA, Journal Year: 2023, Volume and Issue: 329(15), P. 1290 - 1290

Published: April 18, 2023

Importance Skin cancer is the most commonly diagnosed in US. There are different types of skin varying disease incidence and severity. Basal squamous cell carcinomas common but infrequently lead to death or substantial morbidity. Melanomas represent about 1% cause deaths. Melanoma 30 times more White persons than Black persons. However, with darker color often at later stages, when difficult treat. Objective To update its 2016 recommendation, US Preventive Services Task Force (USPSTF) commissioned a systematic review on benefits harms screening for asymptomatic adolescents adults. Population Asymptomatic adults who do not have history premalignant malignant lesions. Evidence Assessment The USPSTF concludes that evidence insufficient determine balance visual examination by clinician screen Recommendation current assess (I statement)

Language: Английский

Citations

59
Predicting skin cancer risk from facial images with an explainable artificial intelligence (XAI) based approach: a proof-of-concept study DOI Creative Commons
Xianjing Liu, Tobias E. Sangers, Tamar Nijsten

et al.

EClinicalMedicine, Journal Year: 2024, Volume and Issue: 71, P. 102550 - 102550

Published: March 19, 2024

Efficient identification of individuals at high risk skin cancer is crucial for implementing personalized screening strategies and subsequent care. While Artificial Intelligence holds promising potential predictive analysis using image data, its application prediction utilizing facial images remains unexplored. We present a neural network-based explainable artificial intelligence (XAI) approach based on 2D compare efficacy to 18 established factors data from the Rotterdam Study.

Language: Английский

Citations

10
Longer survival from melanoma in Germany DOI
Nora Eisemann,

Laura Schumann,

Hannah Baltus

et al.

Deutsches Ärzteblatt international, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 16, 2024

New treatment options for cutaneous melanomas with a poor prognosis have been available since 2011, including immune therapies and targeted drugs. Randomized controlled trials demonstrated that these treatments improve survival, but no population- level studies to date.

Language: Английский

Citations

8
Performance of Commercial Dermatoscopic Systems That Incorporate Artificial Intelligence for the Identification of Melanoma in General Practice: A Systematic Review DOI Open Access
Ian Miller, Nedeljka Rosić,

Michael Stapelberg

et al.

Cancers, Journal Year: 2024, Volume and Issue: 16(7), P. 1443 - 1443

Published: April 8, 2024

Cutaneous melanoma remains an increasing global public health burden, particularly in fair-skinned populations. Advancing technologies, artificial intelligence (AI), may provide additional tool for clinicians to help detect malignancies with a more accurate success rate. This systematic review aimed report the performance metrics of commercially available convolutional neural networks (CNNs) tasked detecting MM. A literature search was performed using CINAHL, Medline, Scopus, ScienceDirect and Web Science databases. total 16 articles reporting MM were included this review. The combined number melanomas detected 1160, non-melanoma lesions 33,010. market-approved technology clinician classifying highly heterogeneous, sensitivity ranging from 16.4 100.0%, specificity between 40.0 98.3% accuracy 44.0 92.0%. Less heterogeneity observed when worked unison AI, 83.3 83.7 87.3%, 86.4 86.9%. Instead focusing on AI versus melanoma, consistent has been obtained clinicians' work is supported by facilitating management decisions improving outcomes.

Language: Английский

Citations

6
Proposed Visual Explainable model in Melanoma Detection and Risk Prediction using Modified ResNet50 DOI Creative Commons

Sarvachan Verma,

Ajitesh Kumar, Manoj Kumar

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

Abstract This study proposed an enhanced visual explainable model for melanoma detection and risk prediction. We utilized the HAM10000 dataset, applying pre-processing techniques to improve image quality. Feature extraction segmentation were performed using a U-Net model-based Dual Stream CNN-Transformer technique. selection was optimized Henry Gas Solubility Optimization (HGSO) algorithm Water Strider Algorithm (WSA). A Deep Learning Model (DLM), specifically Optimal Multi-Attention Fusion (MAF) ConvNeXt, trained detection. For disease severity prediction, we introduced Modified ResNet-50 combined with Explainable AI technique Grad-CAM, providing explanations model's predictions. Experimental results demonstrate robust classification performance AUC of 0.997, recall 99%, precision 99.5%. aims diagnose accurate, efficient, assessment. The source code can be accessed at https://github.com/SarvachanVerma/Visual-Explanible-code-for-Melanoma_Matlab

Language: Английский

Citations

0
The USPSTF I Statement on Skin Cancer Screening—Not a Disappointment but an Opportunity DOI
Adewole S. Adamson

JAMA Dermatology, Journal Year: 2023, Volume and Issue: 159(6), P. 579 - 579

Published: April 18, 2023

Our website uses cookies to enhance your experience. By continuing use our site, or clicking "Continue," you are agreeing Cookie Policy | Continue JAMA Dermatology HomeNew OnlineCurrent IssueFor Authors Podcast Journals Network Open Cardiology Health Forum Internal Medicine Neurology Oncology Ophthalmology Otolaryngology–Head & Neck Surgery Pediatrics Psychiatry Archives of (1919-1959) JN Learning / CMESubscribeJobsInstitutions LibrariansReprints Permissions Terms Use Privacy Accessibility Statement 2023 American Medical Association. All Rights Reserved Search Archive Input Term Sign In Individual inCreate an Account Access through institution Purchase Options: Buy this article Rent Subscribe the journal

Language: Английский

Citations

8
Implementing systematic melanoma risk assessment and risk‐tailored surveillance in a skin cancer focussed dermatology clinic: A qualitative study of feasibility and acceptability to patients and clinic staff DOI Creative Commons
Andrea L. Smith, Amelia K. Smit, Bela I. Laginha

et al.

Cancer Medicine, Journal Year: 2024, Volume and Issue: 13(2)

Published: Jan. 1, 2024

International bodies recommend that melanoma risk assessment should be integrated into skin cancer care provision, but evidence to support implementation is lacking.

Language: Английский

Citations

2
Insufficient Evidence for Screening Reinforces Need for Primary Prevention of Skin Cancer DOI Open Access
Isabella de Vere Hunt, Jenna Lester, Eleni Linos

et al.

JAMA Internal Medicine, Journal Year: 2023, Volume and Issue: 183(6), P. 509 - 509

Published: April 18, 2023

Our website uses cookies to enhance your experience. By continuing use our site, or clicking "Continue," you are agreeing Cookie Policy | Continue JAMA Internal Medicine HomeNew OnlineCurrent IssueFor Authors Podcast Journals Network Open Cardiology Dermatology Health Forum Neurology Oncology Ophthalmology Otolaryngology–Head & Neck Surgery Pediatrics Psychiatry Archives of (1919-1959) JN Learning / CMESubscribeJobsInstitutions LibrariansReprints Permissions Terms Use Privacy Accessibility Statement 2023 American Medical Association. All Rights Reserved Search Archive Input Term Sign In Individual inCreate an Account Access through institution Purchase Options: Buy this article Rent Subscribe the journal

Language: Английский

Citations

4
Extracellular Vesicles in the Skin Microenvironment: Emerging Roles as Biomarkers and Therapeutic Tools in Dermatologic Health and Disease DOI Creative Commons
Joseph P. Flemming, Peter J. Wermuth, Mỹ G. Mahoney

et al.

Journal of Investigative Dermatology, Journal Year: 2023, Volume and Issue: 144(2), P. 225 - 233

Published: Oct. 24, 2023

Language: Английский

Citations

4
Evaluation of a Population-Based Targeted Screening Approach for Skin Cancer with Long-Time Follow-Up in Austria including Potential Effects on Melanoma Mortality DOI Open Access
Wolfgang Brozek, Patrick Clemens, Hanno Ulmer

et al.

Cancers, Journal Year: 2024, Volume and Issue: 16(7), P. 1283 - 1283

Published: March 26, 2024

Background: whether screening for skin cancer affects melanoma-specific mortality in a population-based setting remains unclear. Methods: this cohort study, we characterized and evaluated prevention program following targeted approach conducted 1989–1994 the Austrian province Vorarlberg, with follow-up until 2019. The general population attendees of health examination served comparison. Results: including full 2019, 207 invasive 187 situ melanomas were identified 8997 individuals. Incidences elevated compared to (IRR 2.92, 95%-CI 2.49–3.41, IRR 4.13, 3.53–4.83, respectively) (HR 3.02, 2.59–3.52, HR 3.90, 3.30–4.61, respectively). Breslow thickness Clark’s level at time diagnosis significantly lower 1989–2019, but tumor characteristics diagnosed during did not differ from comparison groups. Moreover, melanoma was 1.66, 1.00–2.75 vs. population, 2.12, 1.25–3.61 cohort). Melanoma Vorarlberg declined 2004, though statistically non-significantly. Conclusions: given uncertain effectiveness high public expenditures population-wide mass programs, primary risk-based might be promising alternatives.

Language: Английский

Citations

1