IDEAS home Printed from https://ideas.repec.org/r/nat/nature/v546y2017i7660d10.1038_nature22985.html
   My bibliography  Save this item

Correction: Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. von Walter, Benjamin & Wentzel, Daniel & Raff, Stefan, 2023. "Should service firms introduce algorithmic advice to their existing customers? The moderating effect of service relationships," Journal of Retailing, Elsevier, vol. 99(2), pages 280-296.
  2. Mendes, Carlos Frederico S. da F. & Krohling, Renato A., 2022. "Deep and handcrafted features from clinical images combined with patient information for skin cancer diagnosis," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
  3. Romain Cadario & Chiara Longoni & Carey K. Morewedge, 2021. "Understanding, explaining, and utilizing medical artificial intelligence," Nature Human Behaviour, Nature, vol. 5(12), pages 1636-1642, December.
  4. Olga Vl. Bitkina & Jaehyun Park & Jungyoon Kim, 2022. "Modeling Sleep Quality Depending on Objective Actigraphic Indicators Based on Machine Learning Methods," IJERPH, MDPI, vol. 19(16), pages 1-14, August.
  5. Samantha Ouellette & Babar K. Rao, 2022. "Usefulness of Smartphones in Dermatology: A US-Based Review," IJERPH, MDPI, vol. 19(6), pages 1-14, March.
  6. Yun-Tsan Chang & Pacôme Prompsy & Susanne Kimeswenger & Yi-Chien Tsai & Desislava Ignatova & Olesya Pavlova & Christoph Iselin & Lars E. French & Mitchell P. Levesque & François Kuonen & Malgorzata Bo, 2024. "MHC-I upregulation safeguards neoplastic T cells in the skin against NK cell-mediated eradication in mycosis fungoides," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
  7. Yasir Adil Mukhlif & Nehad T. A. Ramaha & Alaa Ali Hameed & Mohammad Salman & Dong Keon Yon & Norma Latif Fitriyani & Muhammad Syafrudin & Seung Won Lee, 2024. "Ant Colony and Whale Optimization Algorithms Aided by Neural Networks for Optimum Skin Lesion Diagnosis: A Thorough Review," Mathematics, MDPI, vol. 12(7), pages 1-29, March.
  8. Hanning Ying & Xiaoqing Liu & Min Zhang & Yiyue Ren & Shihui Zhen & Xiaojie Wang & Bo Liu & Peng Hu & Lian Duan & Mingzhi Cai & Ming Jiang & Xiangdong Cheng & Xiangyang Gong & Haitao Jiang & Jianshuai, 2024. "A multicenter clinical AI system study for detection and diagnosis of focal liver lesions," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
  9. Anran Wang & Xiaolei Xiu & Shengyu Liu & Qing Qian & Sizhu Wu, 2022. "Characteristics of Artificial Intelligence Clinical Trials in the Field of Healthcare: A Cross-Sectional Study on ClinicalTrials.gov," IJERPH, MDPI, vol. 19(20), pages 1-20, October.
  10. Wentong Zhou & Ziheng Deng & Yong Liu & Hui Shen & Hongwen Deng & Hongmei Xiao, 2022. "Global Research Trends of Artificial Intelligence on Histopathological Images: A 20-Year Bibliometric Analysis," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
  11. Lin Lu & Laurent Dercle & Binsheng Zhao & Lawrence H. Schwartz, 2021. "Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
  12. Jamil Ahmad & Abdul Khader Jilani Saudagar & Khalid Mahmood Malik & Waseem Ahmad & Muhammad Badruddin Khan & Mozaherul Hoque Abul Hasanat & Abdullah AlTameem & Mohammed AlKhathami & Muhammad Sajjad, 2022. "Disease Progression Detection via Deep Sequence Learning of Successive Radiographic Scans," IJERPH, MDPI, vol. 19(1), pages 1-16, January.
  13. Sangwon Chae & Sungjun Kwon & Donghyun Lee, 2018. "Predicting Infectious Disease Using Deep Learning and Big Data," IJERPH, MDPI, vol. 15(8), pages 1-20, July.
  14. Cristian Simionescu & Adrian Iftene, 2022. "Deep Learning Research Directions in Medical Imaging," Mathematics, MDPI, vol. 10(23), pages 1-25, November.
  15. Zheng Yan & Wenqian Robertson & Yaosheng Lou & Tom W. Robertson & Sung Yong Park, 2021. "Finding leading scholars in mobile phone behavior: a mixed-method analysis of an emerging interdisciplinary field," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9499-9517, December.
  16. Songhee Cheon & Jungyoon Kim & Jihye Lim, 2019. "The Use of Deep Learning to Predict Stroke Patient Mortality," IJERPH, MDPI, vol. 16(11), pages 1-12, May.
  17. Freddy Gabbay & Rotem Lev Aharoni & Ori Schweitzer, 2022. "Deep Neural Network Memory Performance and Throughput Modeling and Simulation Framework," Mathematics, MDPI, vol. 10(21), pages 1-20, November.
  18. Jingui Zhang & Chuangji Meng & Cunlu Xu & Jingyong Ma & Wei Su, 2022. "Deep Transfer Learning Method Based on Automatic Domain Alignment and Moment Matching," Mathematics, MDPI, vol. 10(14), pages 1-14, July.
  19. Rasheed Omobolaji Alabi & Alhadi Almangush & Mohammed Elmusrati & Ilmo Leivo & Antti Mäkitie, 2022. "Measuring the Usability and Quality of Explanations of a Machine Learning Web-Based Tool for Oral Tongue Cancer Prognostication," IJERPH, MDPI, vol. 19(14), pages 1-13, July.
  20. Yuming Jiang & Zhicheng Zhang & Wei Wang & Weicai Huang & Chuanli Chen & Sujuan Xi & M. Usman Ahmad & Yulan Ren & Shengtian Sang & Jingjing Xie & Jen-Yeu Wang & Wenjun Xiong & Tuanjie Li & Zhen Han & , 2023. "Biology-guided deep learning predicts prognosis and cancer immunotherapy response," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  21. Md Tauhidul Islam & Zixia Zhou & Hongyi Ren & Masoud Badiei Khuzani & Daniel Kapp & James Zou & Lu Tian & Joseph C. Liao & Lei Xing, 2023. "Revealing hidden patterns in deep neural network feature space continuum via manifold learning," Nature Communications, Nature, vol. 14(1), pages 1-20, December.
  22. Marta Mazur & Artnora Ndokaj & Divyambika Catakapatri Venugopal & Michela Roberto & Cristina Albu & Maciej Jedliński & Silverio Tomao & Iole Vozza & Grzegorz Trybek & Livia Ottolenghi & Fabrizio Guerr, 2021. "In Vivo Imaging-Based Techniques for Early Diagnosis of Oral Potentially Malignant Disorders—Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 18(22), pages 1-22, November.
  23. Chinmay Belthangady & Stefanos Giampanis & Ivana Jankovic & Will Stedden & Paula Alves & Stephanie Chong & Charlotte Knott & Beau Norgeot, 2022. "Causal deep learning reveals the comparative effectiveness of antihyperglycemic treatments in poorly controlled diabetes," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
  24. Podobnik, Boris & Dabić, Marina & Wild, Dorian & Di Matteo, Tiziana, 2023. "The impact of STEM on the growth of wealth at varying scales, ranging from individuals to firms and countries: The performance of STEM firms during the pandemic across different markets," Technology in Society, Elsevier, vol. 72(C).
  25. Zhiming Cui & Yu Fang & Lanzhuju Mei & Bojun Zhang & Bo Yu & Jiameng Liu & Caiwen Jiang & Yuhang Sun & Lei Ma & Jiawei Huang & Yang Liu & Yue Zhao & Chunfeng Lian & Zhongxiang Ding & Min Zhu & Dinggan, 2022. "A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
  26. Chowdhury, Emon Kalyan, 2019. "Use of Artificial Intelligence in Stock Trading," MPRA Paper 118175, University Library of Munich, Germany, revised 18 Apr 2019.
  27. Andreas Fügener & Jörn Grahl & Alok Gupta & Wolfgang Ketter, 2022. "Cognitive Challenges in Human–Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation," Information Systems Research, INFORMS, vol. 33(2), pages 678-696, June.
  28. Adityanarayanan Radhakrishnan & Max Ruiz Luyten & Neha Prasad & Caroline Uhler, 2023. "Transfer Learning with Kernel Methods," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  29. Victor Olsavszky & Mihnea Dosius & Cristian Vladescu & Johannes Benecke, 2020. "Time Series Analysis and Forecasting with Automated Machine Learning on a National ICD-10 Database," IJERPH, MDPI, vol. 17(14), pages 1-17, July.
  30. Hsiang-Chun Dong & Hsiang-Kai Dong & Mu-Hsien Yu & Yi-Hsin Lin & Cheng-Chang Chang, 2020. "Using Deep Learning with Convolutional Neural Network Approach to Identify the Invasion Depth of Endometrial Cancer in Myometrium Using MR Images: A Pilot Study," IJERPH, MDPI, vol. 17(16), pages 1-18, August.
  31. Broekhuizen, Thijs & Dekker, Henri & de Faria, Pedro & Firk, Sebastian & Nguyen, Dinh Khoi & Sofka, Wolfgang, 2023. "AI for managing open innovation: Opportunities, challenges, and a research agenda," Journal of Business Research, Elsevier, vol. 167(C).
  32. Khalid A. Ibrahim & Kristin S. Grußmayer & Nathan Riguet & Lely Feletti & Hilal A. Lashuel & Aleksandra Radenovic, 2023. "Label-free identification of protein aggregates using deep learning," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  33. Jungyoon Kim & Jihye Lim, 2021. "A Deep Neural Network-Based Method for Prediction of Dementia Using Big Data," IJERPH, MDPI, vol. 18(10), pages 1-13, May.
  34. Vidhya V. & Anjan Gudigar & U. Raghavendra & Ajay Hegde & Girish R. Menon & Filippo Molinari & Edward J. Ciaccio & U. Rajendra Acharya, 2021. "Automated Detection and Screening of Traumatic Brain Injury (TBI) Using Computed Tomography Images: A Comprehensive Review and Future Perspectives," IJERPH, MDPI, vol. 18(12), pages 1-29, June.
  35. Chee Keong Wee & Xujuan Zhou & Ruiliang Sun & Raj Gururajan & Xiaohui Tao & Yuefeng Li & Nathan Wee, 2022. "Triaging Medical Referrals Based on Clinical Prioritisation Criteria Using Machine Learning Techniques," IJERPH, MDPI, vol. 19(12), pages 1-13, June.
  36. Zahlan, Ahmed & Ranjan, Ravi Prakash & Hayes, David, 2023. "Artificial intelligence innovation in healthcare: Literature review, exploratory analysis, and future research," Technology in Society, Elsevier, vol. 74(C).
  37. Gang Yu & Kai Sun & Chao Xu & Xing-Hua Shi & Chong Wu & Ting Xie & Run-Qi Meng & Xiang-He Meng & Kuan-Song Wang & Hong-Mei Xiao & Hong-Wen Deng, 2021. "Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
  38. DonHee Lee & Seong No Yoon, 2021. "Application of Artificial Intelligence-Based Technologies in the Healthcare Industry: Opportunities and Challenges," IJERPH, MDPI, vol. 18(1), pages 1-18, January.
  39. Pujin Wang & Jianzhuang Xiao & Ken’ichi Kawaguchi & Lichen Wang, 2022. "Automatic Ceiling Damage Detection in Large-Span Structures Based on Computer Vision and Deep Learning," Sustainability, MDPI, vol. 14(6), pages 1-24, March.
  40. Hailong He & Christine Schönmann & Mathias Schwarz & Benedikt Hindelang & Andrei Berezhnoi & Susanne Annette Steimle-Grauer & Ulf Darsow & Juan Aguirre & Vasilis Ntziachristos, 2022. "Fast raster-scan optoacoustic mesoscopy enables assessment of human melanoma microvasculature in vivo," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
  41. Jasper Tromp & David Bauer & Brian L. Claggett & Matthew Frost & Mathias Bøtcher Iversen & Narayana Prasad & Mark C. Petrie & Martin G. Larson & Justin A. Ezekowitz & Scott D. Solomon, 2022. "A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
  42. Kuofeng Hung & Andy Wai Kan Yeung & Ray Tanaka & Michael M. Bornstein, 2020. "Current Applications, Opportunities, and Limitations of AI for 3D Imaging in Dental Research and Practice," IJERPH, MDPI, vol. 17(12), pages 1-18, June.
  43. Soualihou Ngnamsie Njimbouom & Kwonwoo Lee & Jeong-Dong Kim, 2022. "MMDCP: Multi-Modal Dental Caries Prediction for Decision Support System Using Deep Learning," IJERPH, MDPI, vol. 19(17), pages 1-16, September.
  44. Xu Gong & Keqin Guan & Qiyang Chen, 2022. "The role of textual analysis in oil futures price forecasting based on machine learning approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(10), pages 1987-2017, October.
  45. Misagh Faezipour & Miad Faezipour & Saba Pourreza, 2023. "Resiliency and Risk Assessment of Smart Vision-Based Skin Screening Applications with Dynamics Modeling," Sustainability, MDPI, vol. 15(18), pages 1-19, September.
  46. Huang, Xiaozhi & Wu, Xitong & Cao, Xin & Wu, Jifei, 2023. "The effect of medical artificial intelligence innovation locus on consumer adoption of new products," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
  47. Claus Zippel & Sabine Bohnet-Joschko, 2021. "Rise of Clinical Studies in the Field of Machine Learning: A Review of Data Registered in ClinicalTrials.gov," IJERPH, MDPI, vol. 18(10), pages 1-14, May.
  48. Han Xu & Dashan Shang & Qing Luo & Junjie An & Yue Li & Shuyu Wu & Zhihong Yao & Woyu Zhang & Xiaoxin Xu & Chunmeng Dou & Hao Jiang & Liyang Pan & Xumeng Zhang & Ming Wang & Zhongrui Wang & Jianshi Ta, 2023. "A low-power vertical dual-gate neurotransistor with short-term memory for high energy-efficient neuromorphic computing," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  49. Ameera S. Jaradat & Rabia Emhamed Al Mamlook & Naif Almakayeel & Nawaf Alharbe & Ali Saeed Almuflih & Ahmad Nasayreh & Hasan Gharaibeh & Mohammad Gharaibeh & Ali Gharaibeh & Hanin Bzizi, 2023. "Automated Monkeypox Skin Lesion Detection Using Deep Learning and Transfer Learning Techniques," IJERPH, MDPI, vol. 20(5), pages 1-20, March.
  50. Dario Sipari & Betsy D. M. Chaparro-Rico & Daniele Cafolla, 2022. "SANE (Easy Gait Analysis System): Towards an AI-Assisted Automatic Gait-Analysis," IJERPH, MDPI, vol. 19(16), pages 1-27, August.
  51. Cemal Erdem & Arnab Mutsuddy & Ethan M. Bensman & William B. Dodd & Michael M. Saint-Antoine & Mehdi Bouhaddou & Robert C. Blake & Sean M. Gross & Laura M. Heiser & F. Alex Feltus & Marc R. Birtwistle, 2022. "A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
  52. Zijing Wu & Ce Zhang & Xiaowei Gu & Isla Duporge & Lacey F. Hughey & Jared A. Stabach & Andrew K. Skidmore & J. Grant C. Hopcraft & Stephen J. Lee & Peter M. Atkinson & Douglas J. McCauley & Richard L, 2023. "Deep learning enables satellite-based monitoring of large populations of terrestrial mammals across heterogeneous landscape," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
  53. Zilong Zhou & Hang Yuan & Xin Cai, 2023. "Rock Thin Section Image Identification Based on Convolutional Neural Networks of Adaptive and Second-Order Pooling Methods," Mathematics, MDPI, vol. 11(5), pages 1-27, March.
  54. Dani Kiyasseh & Aaron Cohen & Chengsheng Jiang & Nicholas Altieri, 2024. "A framework for evaluating clinical artificial intelligence systems without ground-truth annotations," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  55. Julian Schiele & Thomas Koperna & Jens O. Brunner, 2021. "Predicting intensive care unit bed occupancy for integrated operating room scheduling via neural networks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(1), pages 65-88, February.
  56. Taneja, Anu & Arora, Anuja, 2019. "Modeling user preferences using neural networks and tensor factorization model," International Journal of Information Management, Elsevier, vol. 45(C), pages 132-148.
  57. Kai Feng & Han Hong & Ke Tang & Jingyuan Wang, 2023. "Statistical Tests for Replacing Human Decision Makers with Algorithms," Papers 2306.11689, arXiv.org.
  58. Marios Constantinou & Themis Exarchos & Aristidis G. Vrahatis & Panagiotis Vlamos, 2023. "COVID-19 Classification on Chest X-ray Images Using Deep Learning Methods," IJERPH, MDPI, vol. 20(3), pages 1-13, January.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.