Melanoma

How artificial intelligence is transforming melanoma detection, diagnosis, and treatment.

69 Papers Open Access

Showing all 69 papers

Cited by 19589
Dermatologist-level classification of skin cancer with deep neural networks.

Nature, 2017

Open Access
Cited by 3434
An immunogenic personal neoantigen vaccine for patients with melanoma.

Nature, 2017

Open Access
Cited by 923
A methodological approach to the classification of dermoscopy images.

Comput Med Imaging Graph, 2007

Open Access
Cited by 806
Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network.

Sensors (Basel), 2018

Open Access
Cited by 793
Skin Cancer Detection: A Review Using Deep Learning Techniques.

Int J Environ Res Public Health, 2021

Open Access
Cited by 662
Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study

Lancet Oncol, 2019

Open Access
Cited by 564
Lesion border detection in dermoscopy images.

Comput Med Imaging Graph, 2009

Open Access
Cited by 488
Cross-cohort gut microbiome associations with immune checkpoint inhibitor response in advanced melanoma

Nat Med, 2022

Open Access
Cited by 464
Detection of Skin Cancer Based on Skin Lesion Images Using Deep Learning.

Healthcare (Basel), 2022

Open Access
Cited by 447
Classification of skin lesions using transfer learning and augmentation with Alex-net.

PLoS One, 2019

Open Access
Cited by 374
Results of the 2016 International Skin Imaging Collaboration ISBI Challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images

J Am Acad Dermatol, 2018

Open Access
Cited by 363
Skin Lesion Segmentation in Dermoscopic Images with Combination of YOLO and GrabCut Algorithm.

Diagnostics (Basel), 2019

Open Access
Cited by 343
The Development of a Skin Cancer Classification System for Pigmented Skin Lesions Using Deep Learning

Biomolecules, 2020

Open Access
Cited by 329
Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes.

Skin Res Technol, 2005

Open Access
Cited by 324
Melanoma diagnosis using deep learning techniques on dermatoscopic images.

BMC Med Imaging, 2021

Open Access
Cited by 314
Skin Lesion Segmentation and Multiclass Classification Using Deep Learning Features and Improved Moth Flame Optimization

Diagnostics (Basel), 2021

Open Access
Cited by 225
Classification of Skin Lesions into Seven Classes Using Transfer Learning with AlexNet.

J Digit Imaging, 2020

Open Access
Cited by 220
Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective.

Front Med (Lausanne), 2020

Open Access
Cited by 211
Using machine learning algorithms to predict immunotherapy response in patients with advanced melanoma

Clin Cancer Res, 2021

Open Access
Cited by 207
Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM)

Asian Pac J Cancer Prev, 2019

Open Access
Cited by 203
Melanoma and Nevus Skin Lesion Classification Using Handcraft and Deep Learning Feature Fusion via Mutual Information Measures

Entropy (Basel), 2020

Open Access
Cited by 198
Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma.

Nat Commun, 2024

Open Access
Cited by 191
Independent histogram pursuit for segmentation of skin lesions.

IEEE Trans Biomed Eng, 2008

Open Access
Cited by 185
Smartphone applications for triaging adults with skin lesions that are suspicious for melanoma.

Cochrane Database Syst Rev, 2018

Open Access
Cited by 175
BCN20000: Dermoscopic Lesions in the Wild.

Sci Data, 2024

Open Access
Cited by 166
Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults

Cochrane Database Syst Rev, 2018

Open Access
Cited by 165
Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge

Lancet Digit Health, 2022

Open Access
Cited by 164
Acral melanoma detection using a convolutional neural network for dermoscopy images.

PLoS One, 2018

Open Access
Cited by 159
A multimodal vision foundation model for clinical dermatology.

Nat Med, 2025

Open Access
Cited by 157
Optical Technologies for the Improvement of Skin Cancer Diagnosis: A Review.

Sensors (Basel), 2021

Open Access
Cited by 156
A systematic review and meta-analysis of artificial intelligence versus clinicians for skin cancer diagnosis

NPJ Digit Med, 2024

Open Access
Cited by 155
Deep learning based on standard H&E images of primary melanoma tumors identifies patients at risk for visceral recurrence and death

Clin Cancer Res, 2020

Open Access
Cited by 155
SCDNet: A Deep Learning-Based Framework for the Multiclassification of Skin Cancer Using Dermoscopy Images

Sensors (Basel), 2022

Open Access
Cited by 143
A reinforcement learning model for AI-based decision support in skin cancer.

Nat Med, 2023

Open Access
Cited by 138
Evolution of delayed resistance to immunotherapy in a melanoma responder.

Nat Med, 2021

Open Access
Cited by 137
Advances in melanoma: epidemiology, diagnosis, and prognosis

Front Med (Lausanne), 2023

Open Access
Cited by 127
Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017

J Am Acad Dermatol, 2020

Open Access
Cited by 127
Computer-Aided Diagnosis of Skin Lesions Using Conventional Digital Photography: A Reliability and Feasibility Study

PLoS One, 2013

Open Access
Cited by 126
Prognostic value of B cells in cutaneous melanoma.

Genome Med, 2019

Open Access
Cited by 117
Prognostic significance of deregulated microRNAs in uveal melanomas.

Mol Med Rep, 2019

Open Access
Cited by 116
Identification of Core Genes and Pathways in Melanoma Metastasis via Bioinformatics Analysis.

Int J Mol Sci, 2022

Open Access
Cited by 104
Differential Volatile Signatures from Skin, Naevi and Melanoma: A Novel Approach to Detect a Pathological Process

PLoS One, 2010

Open Access
Cited by 103
Analysis of Artificial Intelligence-Based Approaches Applied to Non-Invasive Imaging for Early Detection of Melanoma: A Systematic Review

Cancers (Basel), 2023

Open Access
Cited by 103
Artificial Intelligence and Its Effect on Dermatologists' Accuracy in Dermoscopic Melanoma Image Classification: Web-Based Survey Study

J Med Internet Res, 2020

Open Access
Cited by 99
Small extracellular vesicles convey the stress-induced adaptive responses of melanoma cells.

Sci Rep, 2019

Open Access
Cited by 90
Topological Tumor Graphs: A Graph-Based Spatial Model to Infer Stromal Recruitment for Immunosuppression in Melanoma

Cancer Res, 2020

Open Access
Cited by 88
Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly-metastatic melanoma

Cell Syst, 2021

Open Access
Cited by 85
A Review of Current and Pipeline Drugs for Treatment of Melanoma

Pharmaceuticals (Basel), 2024

Open Access
Cited by 85
Pyroptosis-Related Gene Signatures Can Robustly Diagnose Skin Cutaneous Melanoma and Predict the Prognosis

Front Oncol, 2021

Open Access
Cited by 83
Melanoma Early Detection: Big Data, Bigger Picture

J Invest Dermatol, 2019

Open Access
Cited by 81
High accuracy label-free classification of single-cell kinetic states from holographic cytometry of human melanoma cells

Sci Rep, 2017

Open Access
Cited by 80
Integrative Analysis of Long Noncoding RNA (lncRNA), microRNA (miRNA) and mRNA Expression and Construction of a Competing Endogenous RNA (ceRNA) Network in Metastatic Melanoma

Med Sci Monit, 2019

Open Access
Cited by 76
Recognition of Cutaneous Melanoma on Digitized Histopathological Slides via Artificial Intelligence Algorithm

Front Oncol, 2020

Open Access
Cited by 74
Identification of key candidate genes involved in melanoma metastasis.

Mol Med Rep, 2019

Open Access
Cited by 73
The Value of Total Body Photography for the Early Detection of Melanoma: A Systematic Review.

Int J Environ Res Public Health, 2021

Open Access
Cited by 72
The Long Non-Coding RNA RHPN1-AS1 Promotes Uveal Melanoma Progression.

Int J Mol Sci, 2017

Open Access
Cited by 71
Plasma-derived extracellular vesicle analysis and deconvolution enable prediction and tracking of melanoma checkpoint blockade outcome

Sci Adv, 2020

Open Access
Cited by 69
Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma

Sci Rep, 2019

Open Access
Cited by 67
Performance of a deep neural network in teledermatology: a single-centre prospective diagnostic study

J Eur Acad Dermatol Venereol, 2021

Open Access
Cited by 58
Frequency and implications of discordant gene expression profile class when posterior uveal melanomas are sampled by fine needle aspiration biopsy at two sites

Am J Ophthalmol, 2015

Open Access
Cited by 55
Prediction of early-stage melanoma recurrence using clinical and histopathologic features.

NPJ Precis Oncol, 2022

Open Access
Cited by 55
The Role and Potential of 18F-FDG PET/CT in Malignant Melanoma: Prognostication, Monitoring Response to Targeted and Immunotherapy, and Radiomics

Diagnostics (Basel), 2022

Open Access
Cited by 53
DNA methylation-based prediction of response to immune checkpoint inhibition in metastatic melanoma.

J Immunother Cancer, 2021

Open Access
Cited by 53
MicroRNA Ratios Distinguish Melanomas from Nevi.

J Invest Dermatol, 2020

Open Access
Cited by 52
Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases

EBioMedicine, 2023

Open Access
Cited by 48
A Machine learning model trained on dual-energy CT radiomics significantly improves immunotherapy response prediction for patients with stage IV melanoma

J Immunother Cancer, 2021

Open Access
Cited by 40
Radiomics for the noninvasive prediction of the BRAF mutation status in patients with melanoma brain metastases

Neuro Oncol, 2022

Open Access
Cited by 32
Primary Cutaneous Melanoma—Management in 2024

J Clin Med, 2024

Open Access
Cited by 11
Immune Checkpoint Inhibitor Therapy for Metastatic Melanoma: What Should We Focus on to Improve the Clinical Outcomes?

Int J Mol Sci, 2024

Open Access