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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Last data update: May 20, 2024
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Comparing preferences for skin cancer screening: AI-enabled app vs dermatologist.
Susanne Gaube et al. Soc Sci Med 2024 349116871
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Artificial intelligence and skin cancer.
Maria L Wei et al. Front Med (Lausanne) 2024 111331895
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Basic principles of artificial intelligence in dermatology explained using melanoma.
Tim Hartmann et al. J Dtsch Dermatol Ges 2024
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Deep learning models across the range of skin disease.
Kaushik P Venkatesh et al. NPJ Digit Med 2024 7(1) 32
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Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance.
Lucy Thomas et al. Front Med (Lausanne) 2023 101264846
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Artificial Intelligence in Melanoma Dermatopathology: A Review of Literature.
Hannah Neimy et al. Am J Dermatopathol 2023
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Skin cancer diagnosis (SCD) using Artificial Neural Network (ANN) and Improved Gray Wolf Optimization (IGWO).
Wanqi Lai et al. Sci Rep 2023 13(1) 19377
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Analysis of Artificial Intelligence-Based Approaches Applied to Non-Invasive Imaging for Early Detection of Melanoma: A Systematic Review.
Raj H Patel et al. Cancers (Basel) 2023 15(19)
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AI-based skin cancer detection: the balance between access and overutilization
KP Venkatesh et al, NPJ Digital Medicine, August 15, 2023
A comprehensive analysis of recent advancements in cancer detection using machine learning and deep learning models for improved diagnostics.
Hari Mohan Rai et al. J Cancer Res Clin Oncol 2023
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SBXception: A Shallower and Broader Xception Architecture for Efficient Classification of Skin Lesions.
Abid Mehmood et al. Cancers (Basel) 2023 15(14)
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Diagnostic performance of augmented intelligence with 2D and 3D total body photography and convolutional neural networks in a high-risk population for melanoma under real-world conditions: A new era of skin cancer screening?
Sara E Cerminara et al. Eur J Cancer 2023 190112954
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Non-Melanoma Skin Cancer Detection in the Age of Advanced Technology: A Review.
Haleigh Stafford et al. Cancers (Basel) 2023 15(12)
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An artificial intelligence based app for skin cancer detection evaluated in a population based setting.
Anna M Smak Gregoor et al. NPJ Digit Med 2023 6(1) 90
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Assessment of Diagnostic Performance of Dermatologists Cooperating With a Convolutional Neural Network in a Prospective Clinical Study: Human With Machine.
Julia K Winkler et al. JAMA Dermatol 2023
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Exploring the potential of artificial intelligence in improving skin lesion diagnosis in primary care.
Anna Escalé-Besa et al. Scientific reports 2023 13(1) 4293
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Clinical Application of Artificial Intelligence for Non-melanoma Skin Cancer.
Katherine Sanchez et al. Current treatment options in oncology 2023 1-7
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Towards successful implementation of artificial intelligence in skin cancer care: a qualitative study exploring the views of dermatologists and general practitioners.
Sangers Tobias E et al. Archives of dermatological research 2022 1-9
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Automatic Malignant and Benign Skin Cancer Classification Using a Hybrid Deep Learning Approach.
Bassel Atheer et al. Diagnostics (Basel, Switzerland) 2022 12(10)
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Artificial Intelligence in Dermatology: Challenges and Perspectives.
Liopyris Konstantinos et al. Dermatology and therapy 2022
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Deep Convolutional Generative Adversarial Networks to Enhance Artificial Intelligence in Healthcare: A Skin Cancer Application.
La Salvia Marco et al. Sensors (Basel, Switzerland) 2022 22(16)
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Artificial Intelligence in the Detection of Skin Cancer.
Beltrami Eric J et al. Journal of the American Academy of Dermatology 2022
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Over-Detection of Melanoma-Suspect Lesions by a CE-Certified Smartphone App: Performance in Comparison to Dermatologists, 2D and 3D Convolutional Neural Networks in a Prospective Data Set of 1204 Pigmented Skin Lesions Involving Patients' Perception.
Jahn Anna Sophie et al. Cancers 2022 14(15)
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Automatic skin lesions detection from images through microscopic hybrid features set and machine learning classifiers.
Alyami Jaber et al. Microscopy research and technique 2022
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Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review.
Jones O T et al. The Lancet. Digital health 2022 4(6) e466-e476
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Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand Challenge.
Combalia Marc et al. The Lancet. Digital health 2022 4(5) e330-e339
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Explainable artificial intelligence in skin cancer recognition: A systematic review.
Hauser Katja et al. European journal of cancer (Oxford, England : 1990) 2022 16754-69
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A Non-Invasive Interpretable Diagnosis of Melanoma Skin Cancer Using Deep Learning and Ensemble Stacking of Machine Learning Models.
Alfi Iftiaz A et al. Diagnostics (Basel, Switzerland) 2022 12(3)
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Web-Based Skin Cancer Assessment and Classification Using Machine Learning and Mobile Computerized Adaptive Testing in a Rasch Model: Development Study.
Yang Ting-Ya et al. JMIR medical informatics 2022 10(3) e33006
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Evaluation of Artificial Intelligence-assisted Diagnosis of Skin Neoplasms - a single-center, paralleled, unmasked, randomized controlled trial.
Han Seung Seog et al. The Journal of investigative dermatology 2022
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Page last reviewed:
Feb 1, 2024
Page last updated:
May 20, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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