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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. 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.
  3. 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).
  4. 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).
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. Chowdhury, Emon Kalyan, 2019. "Use of Artificial Intelligence in Stock Trading," MPRA Paper 118175, University Library of Munich, Germany, revised 18 Apr 2019.
  11. 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).
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. Samantha Ouellette & Babar K. Rao, 2022. "Usefulness of Smartphones in Dermatology: A US-Based Review," IJERPH, MDPI, vol. 19(6), pages 1-14, March.
  17. 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.
  18. 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.
  19. Daniel Susskind, 2017. "Re-Thinking the Capabilities of Machines in Economics," Economics Series Working Papers 825, University of Oxford, Department of Economics.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. Daniel Susskind, 2019. "Re-thinking the capabilities of technology in economics," Economics Bulletin, AccessEcon, vol. 39(1), pages 280-288.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  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. 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.
  36. 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.
  37. 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.
  38. 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.
  39. 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.
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  41. 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.
  42. 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).
  43. 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.
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