Dermatologist-level classification of skin cancer with deep neural networks

Esteva, Andre, Kuprel, Brett, Novoa, Roberto A., Ko, Justin, Swetter, Susan M., Blau, Helen M., Thrun, Sebastian·2017·Nature
DOI 10.1038/nature21056

Cited by (1,225)

Items 1,201–1,225 of 1,225

  1. Multimodal dual-stage feature refinement for robust skin lesion classification
    Khurshid, Mahapara, Singh, Richa, Vatsa, Mayank · 2025 · Scientific Reports
  2. Uncertainty-aware segmentation quality prediction via deep learning Bayesian Modeling: Comprehensive evaluation and interpretation on skin cancer and liver segmentation
    O.K., Sikha, Riera-Marín, Meritxell, Galdran, Adrian, López, Javier García, Rodríguez-Comas, Júlia, Piella, Gemma, Ballester, Miguel A. González · 2025 · Computerized Medical Imaging and Graphics
  3. Calibration of Model Uncertainty for Dropout Variational Inference
    Laves, Max-Heinrich, Ihler, Sontje, Kortmann, Karl-Philipp, Ortmaier, Tobias · 2020 · arXiv
  4. XAI-based Clinical Decision Support System: A Systematic Review
    Kim, SeYoung, Kim, DaeHo, Kim, MinJi, Ko, HyoJin, Jeong, OkRan · 2024
  5. Identifying Metabolic Syndrome Easily and Cost Effectively Using Non-Invasive Methods with Machine Learning Models
    Xu, Wei, Zhang, Zikai, Hu, Kerong, Fang, Ping, Li, Ran, Kong, Dehong, Xuan, Miao, Yue, Yang, She, Dunmin, Xue, Ying · 2023 · Diabetes, Metabolic Syndrome and Obesity
  6. Assessing the performance of artificial intelligence models in evaluating inflammatory skin disease severity: a systematic review and meta-analysis
    Cai, Zhuo Ran, Kim, Jiyeong, Rezaei, Shawheen J, Chen, Michael L, Touma, Fadi, Zhu, Catherine, Onyeka, Sonia, Fonjungo, Fonette, Omiye, Jesutofunmi A, Krakowski, Isabelle et al. · 2025 · British Journal of Dermatology
  7. Artificial Intelligence in Medical Education- Perception Among Medical Students
    Jackson, Preetha, S, Gayathri P, Babu, Chikku, Tony, Christa, Jack, Deen Stephano, Davis, Dency, R, Reshma V., Kurian, Nisha, John, Anjum · 2024
  8. Multimodal deep learning ensemble framework for skin cancer detection
    Saeed, Mayar Ashraf, Afify, Yasmine M., Badr, Nagwa Lotfy, Helal, Nivin A. · 2025 · Scientific Reports
  9. Recommended requirements and essential elements for proper reporting of the use of artificial intelligence machine learning tools in biomedical research and scientific publications
    Cote, Mark P., Lubowitz, James H. · 2024 · Arthroscopy
  10. Artificial Intelligence in Clinical Oncology: From Productivity Enhancement to Creative Discovery
    Kuno, Masahiro, Osumi, Hiroki, Udagawa, Shohei, Yoshikawa, Kaoru, Ooki, Akira, Shinozaki, Eiji, Ishikawa, Tetsuo, Oba, Junna, Yamaguchi, Kensei, Sakurada, Kazuhiro · 2025 · Current Oncology
  11. EA-FUSION: A multimodal emotion recognition model using EEG and facial expression data
    Xu, Cheng, Li, Wei, Li, Sen, Zhao, Penglu, Xing, Fangyi, Song, Aiguo · 2026 · Biomedical Signal Processing and Control
  12. Artificial intelligence–enabled precision medicine for inflammatory skin diseases
    Tang, Alice S., Wei, Maria L., Haemel, Anna, La, Cindy, Sirota, Marina, Lee, Ernest Y. · 2026 · Journal of Investigative Dermatology
  13. Cutting-edge CNN-based skin cancer detection with batch normalization and advanced imbalance learning for superior medical image classification
    Govindu, Surla, Devi, O.Rama, Sitharam, M., Koreddi, Venkatesh, Kumar, Meriga Kiran, Sunitha, M. · 2026 · Biomedical Signal Processing and Control
  14. Artificial Intelligence-Aided Recognition of Pathological Characteristics and Subtype Classification of Superficial Perivascular Dermatitis
    Bao, Yingqiu, Zhang, Jing, Zhang, Qiuli, Chang, Jianmin, Lu, Di, Fu, Yu · 2021 · Frontiers in Medicine
  15. Skin cancer detection using the HAM10000 dataset: a comparative study of machine learning models
    Velaga, NandaKiran, Vardineni, Venkata Revanth, Tupakula, Phanindra, Pamidimukkala, Jaanaki Swaroop · 2023 · 2023 Global Conference on Information Technologies and Communications (GCITC)
  16. Medical student’s attitudes and perceptions toward artificial intelligence applications
    2022 · Journal for Educators, Teachers and Trainers
  17. A Computer-Aided Diagnosis System of Fetal Nucleated Red Blood Cells With Convolutional Neural Network
    Sun, Chao, Wang, Ruijie, Zhao, Lanbo, Han, Lu, Ma, Sijia, Liang, Dongxin, Wang, Lei, Tuo, Xiaoqian, Zhang, Yu, Zhong, Dexing et al. · 2022 · Archives of Pathology & Laboratory Medicine
  18. Self-supervised artificial intelligence system for differentiating mycosis fungoides and benign inflammatory dermatoses
    Zhao, Jie, Bai, Juan, Li, Guomin, Sun, Qingmiao, Li, Sheng, Wang, Chen, Li, Hui, Xue, Ruzeng, Qiao, Jianjun · 2026 · British Journal of Dermatology
  19. Revamping AI models in dermatology: overcoming critical challenges for enhanced skin lesion diagnosis
    Mehta, Deval, Betz-Stablein, Brigid, Nguyen, Toan D, Gal, Yaniv, Bowling, Adrian, Haskett, Martin, Sashindranath, Maithili, Bonnington, Paul, Mar, Victoria, Soyer, H Peter et al. · 2023 · arXiv
  20. Revolutionizing dermatopathology using AI in skin diagnostics: scoping review
    Rammal, Rawan, Mohy U Din, Ahmad, Alam, Tanvir · 2026 · Frontiers in Medicine
  21. Artificial Intelligence in Clinical Decision-Making: A Comprehensive Review of Diagnostic, Prognostic, and Therapeutic Applications, Validation Gaps, Bias, and Deployment Challenges
    Patil, Saurabh S, Jha, Gaurav Kumar, Mohsin, Naveed, Patel, Pankaj, Ralte, Lalramdinmawia, Shukla, Ashish Kumar · 2026 · Cureus
  22. Prediction of Postoperative ICU Requirements: Closing the Translational Gap with a Real-World Clinical Benchmark for Artificial Intelligence Approaches
    Althammer, Alexander, Berger, Felix, Spring, Oliver, Simon, Philipp, Girrbach, Felix, Dieing, Maximilian, Brunner, Jens O., Shmygalev, Sergey, Bartenschlager, Christina C., Heller, Axel R. · 2025 · Information
  23. Synthesized clinical notes enable training robust multimodal AI models from unimodal dermatology datasets
    Marini, Niccolo, Liang, Zhaohui, Rajaraman, Sivaramakrishnan, Xue, Zhiyun, Antani, Sameer · 2026 · npj Digital Medicine
  24. Entre Códigos y Corazones: Investigación e Inteligencia Artificial hacia una Tecnología más Humana
    Garcia-Heredia, Nepsi Beatriz, Mujica-Sequera, Ruth M. · 2025 · Revista Docentes 2.0
  25. Artificial intelligence and deep learning in ophthalmology
    Ting, Daniel Shu Wei, Pasquale, Louis R, Peng, Lily, Campbell, John Peter, Lee, Aaron Y, Raman, Rajiv, Tan, Gavin Siew Wei, Schmetterer, Leopold, Keane, Pearse A, Wong, Tien Yin · 2019 · British Journal of Ophthalmology