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Dermatologist-level classification of skin cancer with deep neural networks

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  1. Miloš Kotlar & Dragan Bojić & Marija Punt & Veljko Milutinović, 2019. "Survey of deployment locations and underlying hardware architectures for contemporary deep neural networks," International Journal of Distributed Sensor Networks, , vol. 15(8), pages 15501477198, August.
  2. Feng-Ping An, 2019. "Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network," Complexity, Hindawi, vol. 2019, pages 1-15, October.
  3. Wilson Castro & Jimy Oblitas & Roberto Santa-Cruz & Himer Avila-George, 2017. "Multilayer perceptron architecture optimization using parallel computing techniques," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-17, December.
  4. Emily J MacKay & Michael D Stubna & Corey Chivers & Michael E Draugelis & William J Hanson & Nimesh D Desai & Peter W Groeneveld, 2021. "Application of machine learning approaches to administrative claims data to predict clinical outcomes in medical and surgical patient populations," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-14, June.
  5. 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.
  6. 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).
  7. 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.
  8. Joon-myoung Kwon & Ki-Hyun Jeon & Hyue Mee Kim & Min Jeong Kim & Sungmin Lim & Kyung-Hee Kim & Pil Sang Song & Jinsik Park & Rak Kyeong Choi & Byung-Hee Oh, 2019. "Deep-learning-based risk stratification for mortality of patients with acute myocardial infarction," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-15, October.
  9. Mithun S. Ullal & Iqbal Thonse Hawaldar & Suhan Mendon & Nympha Rita Joseph, 2020. "The effect of artificial intelligence on the sales graph in Indian market," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(4), pages 2940-2954, June.
  10. Chetna Dabas & Shikhar Jain & Ashish Bansal & Vaibhav Sharma, 2020. "Implementation of image colorization with convolutional neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 625-634, June.
  11. Samantha Ouellette & Babar K. Rao, 2022. "Usefulness of Smartphones in Dermatology: A US-Based Review," IJERPH, MDPI, vol. 19(6), pages 1-14, March.
  12. 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.
  13. 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.
  14. Daniel Susskind, 2017. "Re-Thinking the Capabilities of Machines in Economics," Economics Series Working Papers 825, University of Oxford, Department of Economics.
  15. 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.
  16. Priti Bansal & Sumit Kumar & Ritesh Srivastava & Saksham Agarwal, 2021. "Using Transfer Learning and Hierarchical Classifier to Diagnose Melanoma From Dermoscopic Images," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 16(2), pages 73-86, April.
  17. 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.
  18. 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.
  19. Antoine Richard & Brice Mayag & François Talbot & Alexis Tsoukias & Yves Meinard, 2020. "What does it mean to provide decision support to a responsible and competent expert?," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 8(3), pages 205-236, November.
  20. Fügener, A. & Grahl, J. & Gupta, A. & Ketter, W., 2019. "Cognitive challenges in human-AI collaboration: Investigating the path towards productive delegation," ERIM Report Series Research in Management ERS-2019-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  21. Juexiao Zhou & Xiaonan He & Liyuan Sun & Jiannan Xu & Xiuying Chen & Yuetan Chu & Longxi Zhou & Xingyu Liao & Bin Zhang & Shawn Afvari & Xin Gao, 2024. "Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
  22. 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.
  23. Mara Giavina-Bianchi & Raquel Machado de Sousa & Vitor Zago de Almeida Paciello & William Gois Vitor & Aline Lissa Okita & Renata Prôa & Gian Lucca dos Santos Severino & Anderson Alves Schinaid & Rafa, 2021. "Implementation of artificial intelligence algorithms for melanoma screening in a primary care setting," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-13, September.
  24. 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.
  25. He, Wenbin & Liu, Ting & Ming, Wuyi & Li, Zongze & Du, Jinguang & Li, Xiaoke & Guo, Xudong & Sun, Peiyan, 2024. "Progress in prediction of remaining useful life of hydrogen fuel cells based on deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  26. 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.
  27. Cristian Simionescu & Adrian Iftene, 2022. "Deep Learning Research Directions in Medical Imaging," Mathematics, MDPI, vol. 10(23), pages 1-25, November.
  28. Seth G. Benzell & Erik Brynjolfsson, 2019. "Digital Abundance and Scarce Genius: Implications for Wages, Interest Rates, and Growth," NBER Working Papers 25585, National Bureau of Economic Research, Inc.
  29. Kai Feng & Han Hong & Ke Tang & Jingyuan Wang, 2019. "Decision Making with Machine Learning and ROC Curves," Papers 1905.02810, arXiv.org.
  30. Kita-Wojciechowska Kinga & Kidziński Łukasz, 2019. "Google Street View image predicts car accident risk," Central European Economic Journal, Sciendo, vol. 6(53), pages 151-163, January.
  31. 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.
  32. 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.
  33. Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021. "Comparing minds and machines: implications for financial stability," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 479-508.
  34. Oded Rotem & Tamar Schwartz & Ron Maor & Yishay Tauber & Maya Tsarfati Shapiro & Marcos Meseguer & Daniella Gilboa & Daniel S. Seidman & Assaf Zaritsky, 2024. "Visual interpretability of image-based classification models by generative latent space disentanglement applied to in vitro fertilization," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
  35. Chen-Ying Hung & Ching-Heng Lin & Tsuo-Hung Lan & Giia-Sheun Peng & Chi-Chun Lee, 2019. "Development of an intelligent decision support system for ischemic stroke risk assessment in a population-based electronic health record database," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-16, March.
  36. 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.
  37. 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.
  38. Sebastian Gehrmann & Franck Dernoncourt & Yeran Li & Eric T Carlson & Joy T Wu & Jonathan Welt & John Foote Jr. & Edward T Moseley & David W Grant & Patrick D Tyler & Leo A Celi, 2018. "Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-19, February.
  39. 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.
  40. Severin Rodler & Gerald Schulz & Alexander Buchner & Christian Stief & Michael Staehler & Jozefina Casuscelli, 2019. "The Role of Digital Biomarkers in Cancer Research and Patient Care," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 17(3), pages 12870-12872, April.
  41. Jordi Munoz-Muriedas, 2021. "Large scale meta-analysis of preclinical toxicity data for target characterisation and hypotheses generation," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-22, June.
  42. 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.
  43. Magdalena K Sobol & Sarah A Finkelstein, 2018. "Predictive pollen-based biome modeling using machine learning," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-29, August.
  44. 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.
  45. Chaoran Li & Fei Xiao & Yaxiang Fan, 2019. "An Approach to State of Charge Estimation of Lithium-Ion Batteries Based on Recurrent Neural Networks with Gated Recurrent Unit," Energies, MDPI, vol. 12(9), pages 1-22, April.
  46. Seung Seog Han & Ik Jun Moon & Seong Hwan Kim & Jung-Im Na & Myoung Shin Kim & Gyeong Hun Park & Ilwoo Park & Keewon Kim & Woohyung Lim & Ju Hee Lee & Sung Eun Chang, 2020. "Assessment of deep neural networks for the diagnosis of benign and malignant skin neoplasms in comparison with dermatologists: A retrospective validation study," PLOS Medicine, Public Library of Science, vol. 17(11), pages 1-21, November.
  47. 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.
  48. 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.
  49. 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).
  50. Fosso Wamba, Samuel & Bawack, Ransome Epie & Guthrie, Cameron & Queiroz, Maciel M. & Carillo, Kevin Daniel André, 2021. "Are we preparing for a good AI society? A bibliometric review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 164(C).
  51. 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.
  52. Chowdhury, Emon Kalyan, 2019. "Use of Artificial Intelligence in Stock Trading," MPRA Paper 118175, University Library of Munich, Germany, revised 18 Apr 2019.
  53. 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.
  54. Daniel Susskind, 2019. "Re-thinking the capabilities of technology in economics," Economics Bulletin, AccessEcon, vol. 39(1), pages 280-288.
  55. 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.
  56. 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.
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  62. Anna Sandström & Jonathan M Snowden & Jonas Höijer & Matteo Bottai & Anna-Karin Wikström, 2019. "Clinical risk assessment in early pregnancy for preeclampsia in nulliparous women: A population based cohort study," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-16, November.
  63. 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.
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