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

Cited by (1,225)

Items 901–1,000 of 1,225

  1. Skin cancer disease images classification using deep learning solutions
    Maad Mohsin Mijwil · 2021 · Multimedia Tools and Applications
  2. FocalMix: Semi-Supervised Learning for 3D Medical Image Detection
    Wang, Dong, Zhang, Yuan, Zhang, Kexin, Wang, Liwei · 2020 · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  3. Deep learning-aided decision support for diagnosis of skin disease across skin tones
    Groh, Matthew, Badri, Omar, Daneshjou, Roxana, Koochek, Arash, Harris, Caleb, Soenksen, Luis R., Doraiswamy, P. Murali, Picard, Rosalind · 2024 · Nature Medicine
  4. Classification of Breast Cancer Histology Images Using Transfer Learning
    Sulaiman Vesal, Nishant Ravikumar, Amirabbas Davari, Stephan Ellmann, Andreas Maier · 2018 · Lecture notes in computer science
  5. Deep Learning Methods and Applications
    Jamil Ahmad, Haleem Farman, Zahoor Jan · 2018 · SpringerBriefs in computer science
  6. Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions
    Vincent Grollemund, Pierre‐François Pradat, Giorgia Querin, François Delbot, Gaétan Le Chat, Jean‐François Pradat‐Peyre, Peter Bede · 2019 · Frontiers in Neuroscience
  7. DermaKNet: Incorporating the Knowledge of Dermatologists to Convolutional Neural Networks for Skin Lesion Diagnosis
    Iván González-Díaz · 2018 · IEEE Journal of Biomedical and Health Informatics
  8. The Use of Deep Learning to Predict Stroke Patient Mortality
    Song-Hee Cheon, Jungyoon Kim, Jihye Lim · 2019 · International Journal of Environmental Research and Public Health
  9. High-throughput proteomics and AI for cancer biomarker discovery
    Qi Xiao, Fangfei Zhang, Luang Xu, Liang Yue, Oi Lian Kon, Yi Zhu, Tiannan Guo · 2021 · Advanced Drug Delivery Reviews
  10. On the Automatic Detection and Classification of Skin Cancer Using Deep Transfer Learning
    Mohammad Fraiwan, Esraa Faouri · 2022 · Sensors
  11. Artificial intelligence innovation in healthcare: Literature review, exploratory analysis, and future research
    Ahmed Zahlan, Ravi Prakash Ranjan, David Hayes · 2023 · Technology in Society
  12. Evaluating Bayesian Deep Learning Methods for Semantic Segmentation
    Jishnu Mukhoti, Yarin Gal · 2018 · arXiv (Cornell University)
  13. DeepSOFA: a continuous acuity score for critically ill patients using clinically interpretable deep learning.
    Shickel, Benjamin, Loftus, Tyler J., Adhikari, Lasith, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra, Rashidi, Parisa · 2019 · Scientific Reports
  14. Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-Scale Lesion Database
    Yan, Ke, Wang, Xiaosong, Lu, Le, Zhang, Ling, Harrison, Adam P., Bagheri, Mohammadhadi, Summers, Ronald M. · 2018 · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  15. A Deep Learning System for Automated Angle-Closure Detection in Anterior Segment Optical Coherence Tomography Images
    Huazhu Fu, Mani Baskaran, Yanwu Xu, Stephen Lin, Damon Wing Kee Wong, Jiang Liu, Tin A. Tun, Meenakshi Mahesh, Shamira Perera, Tin Aung · 2019 · American Journal of Ophthalmology
  16. An End-to-End Multi-Task Deep Learning Framework for Skin Lesion Analysis
    Lei Song, Jianzhe Lin, Z. Jane Wang, Haoqian Wang · 2020 · IEEE Journal of Biomedical and Health Informatics
  17. Application of Big Data Technology for COVID-19 Prevention and Control in China: Lessons and Recommendations
    Jun Wu, Jian Wang, Stephen Nicholas, Elizabeth Maitland, Qiuyan Fan · 2020 · Journal of Medical Internet Research
  18. Deep learning based active learning technique for data annotation and improve the overall performance of classification models
    Sareer Ul Amin, Adnan Hussain, Bumsoo Kim, Sanghyun Seo · 2023 · Expert Systems with Applications
  19. A medical multimodal large language model for future pandemics
    Liu, Fenglin, Zhu, Tingting, Wu, Xian, Yang, Bang, You, Chenyu, Wang, Chenyang, Lu, Lei, Liu, Zhangdaihong, Zheng, Yefeng, Sun, Xu et al. · 2023 · npj Digital Medicine
  20. Performance of an Artificial Multi-observer Deep Neural Network for Fully Automated Segmentation of Polycystic Kidneys
    Timothy Lee Kline, Panagiotis D. Korfiatis, Marie E. Edwards, Jaime D. Blais, Frank S. Czerwiec, Peter C. Harris, Bernard F. King, Vicente E. Torres, Bradley James Erickson · 2017 · Journal of Imaging Informatics in Medicine
  21. Automatic anatomical classification of esophagogastroduodenoscopy images using deep convolutional neural networks
    Hirotoshi Takiyama, Tsuyoshi Ozawa, Soichiro Ishihara, Mitsuhiro Fujishiro, Satoki Shichijo, Shuhei Nomura, Motoi Miura, Tomohiro Tada · 2018 · Scientific Reports
  22. Computer-Aided Diagnosis in Histopathological Images of the Endometrium Using a Convolutional Neural Network and Attention Mechanisms
    Hao Sun, Xianxu Zeng, Tao Xu, Gang Peng, Yutao Ma · 2019 · IEEE Journal of Biomedical and Health Informatics
  23. A vision-based approach for fall detection using multiple cameras and convolutional neural networks: A case study using the UP-Fall detection dataset
    Ricardo Espinosa, Hiram Ponce-Espinosa, Sebastián Gutiérrez, Lourdes Martínez-Villaseñor, Jorge Brieva, Ernesto Moya-Albor · 2019 · Computers in Biology and Medicine
  24. Melanoma Skin Cancer Detection Method Based on Adaptive Principal Curvature, Colour Normalisation and Feature Extraction with the ABCD Rule
    Dang N. H. Thanh, V. B. Surya Prasath, Lê Minh Hiếu, Nguyễn Ngọc Hiền · 2019 · Journal of Imaging Informatics in Medicine
  25. Notice of Retraction: AI Techniques for COVID-19
    Adedoyin A. Hussain, Ouns Bouachir, Fadi Al-Turjman, Moayad Aloqaily · 2020 · IEEE Access · Retracted
  26. Task-Aware Variational Adversarial Active Learning
    Kwanyoung Kim, D. Park, Kwang In Kim, S. Chun · 2020 · Computer Vision and Pattern Recognition
  27. Automated Monkeypox Skin Lesion Detection Using Deep Learning and Transfer Learning Techniques
    Ameera Saleh Jaradat, Rabia Emhamed Al Mamlook, Naif Mana Almakayeel, Nawaf Alharbe, Ali Saeed Almuflih, Ahmad Nawaf Nasayreh, Hasan Gharaibeh, Mohammad A. Gharaibeh, Ali Gharaibeh, Hanin Fawzi Bzizi · 2023 · International Journal of Environmental Research and Public Health
  28. Noninvasive Diagnosis of Nonalcoholic Fatty Liver Disease and Quantification of Liver Fat with Radiofrequency Ultrasound Data Using One-dimensional Convolutional Neural Networks
    Aiguo Han, Michał Byra, Elhamy R. Heba, Michael P. André, John W. Erdman, Rohit Seth Loomba, Claude B. Sirlin, William D. O’Brien · 2020 · Radiology
  29. Addressing class imbalance in deep learning for small lesion detection on medical images
    Alessandro Bria, Claudio Marrocco, Francesco Tortorella · 2020 · Computers in Biology and Medicine
  30. Application of machine learning in ophthalmic imaging modalities
    Yan Tong, Wei Lü, Yue Yu, Yin Shen · 2020 · Eye and Vision
  31. A DE-ANN Inspired Skin Cancer Detection Approach Using Fuzzy C-Means Clustering
    Manoj Kumar, Mohammed Alshehri, Rayed A. AlGhamdi, Purushottam Sharma, Vikas Deep · 2020 · Mobile Networks and Applications
  32. Diagnosis of interproximal caries lesions with deep convolutional neural network in digital bitewing radiographs
    Yusuf Bayraktar, Enes Ayan · 2021 · Clinical Oral Investigations
  33. Advanced Meta-Heuristic Algorithm Based on Particle Swarm and Al-Biruni Earth Radius Optimization Methods for Oral Cancer Detection
    Myriam Hadjouni, Abdelaziz A. Abdelhamid, El‐Sayed M. El‐kenawy, Abdelhameed F. Ibrahim, Marwa Metwally Eid, Mona Mamdouh Jamjoom, Doaa Sami Khafaga · 2023 · IEEE Access
  34. Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology
    Ajay Vikram Singh, Vaisali Chandrasekar, Namuna Paudel, Peter Laux, Andreas Luch, Donato Gemmati, Veronica Tisato, Kirti Sathyananda Prabhu, Shahab Uddin M.S., Sarada Prasad Dakua · 2023 · Biomedicine & Pharmacotherapy
  35. Data-driven subtyping of Parkinson's disease using longitudinal clinical records: a cohort study
    Zhang, Xi, Chou, Jingyuan, Liang, Jian, Xiao, Cao, Zhao, Yize, Sarva, Harini, Henchcliffe, Claire, Wang, Fei · 2019 · Scientific Reports
  36. Keratinocytic Skin Cancer Detection on the Face Using Region-Based Convolutional Neural Network
    Seung Seog Han, Ik Jun Moon, Woohyung Lim, In Suck Suh, Sam Yong Lee, Jung‐Im Na, Seong Hwan Kim, Sung Eun Chang · 2019 · JAMA Dermatology
  37. Deep Learning Analysis of Vibrational Spectra of Bacterial Lysate for Rapid Antimicrobial Susceptibility Testing
    William John Thrift, Sasha Ronaghi, Muntaha Samad, Hong Liang Wei, Dean Gia Nguyen, Antony Superio Cabuslay, Chloe E. Groome, Peter Joseph Santiago, Pierre Baldi, Allon I. Hochbaum et al. · 2020 · ACS Nano
  38. Classification and Predictions of Lung Diseases from Chest X-rays Using MobileNet V2
    Abdelbaki Souid, Nizar Sakli, Hédi Sakli · 2021 · Applied Sciences
  39. Artificial intelligence in the embryology laboratory: a review
    Irene Dimitriadis, Nikica Zaninović, Alejandro Chávez-Badiola, Charles L. Bormann · 2021 · Reproductive BioMedicine Online
  40. A survey, review, and future trends of skin lesion segmentation and classification
    Md. Kamrul Hasan, Md. Asif Ahamad, Choon Hwai Yap, Guang Yang · 2023 · Computers in Biology and Medicine
  41. Artificial intelligence in cancer diagnosis and therapy: Current status and future perspective
    Muhammad Sufyan, Zeeshan Shokat, Usman Ali Ashfaq · 2023 · Computers in Biology and Medicine
  42. The Moral Psychology of Artificial Intelligence
    Bonnefon, Jean-François, Rahwan, Iyad, Shariff, Azim · 2024 · Annual Review of Psychology
  43. Computer vs human: Deep learning versus perceptual training for the detection of neck of femur fractures
    Matthew Adams, Weijia Chen, David Holcdorf, Mark William McCusker, Piers D. L. Howe, Frank Gaillard · 2018 · Journal of Medical Imaging and Radiation Oncology
  44. Deep Learning Methods for Accurate Skin Cancer Recognition and Mobile Application
    Ioannis Kousis, Isidoros Perikos, Ioannis Hatzilygeroudis, Maria K. Virvou · 2022 · Electronics
  45. Advances in cutaneous squamous cell carcinoma
    Mårten C. G. Winge, Laura N. Kellman, Konnie Guo, Jean Yuh Tang, Susan M. Swetter, Sumaira Z. Aasi, Kavita Yang Sarin, Anne Lynn S. Chang, Paul A. Khavari · 2023 · Nature reviews. Cancer
  46. Accurate recognition of colorectal cancer with semi-supervised deep learning on pathological images
    Yu, Gang, Sun, Kai, Xu, Chao, Shi, Xing-Hua, Wu, Chong, Xie, Ting, Meng, Run-Qi, Meng, Xiang-He, Wang, Kuan-Song, Xiao, Hong-Mei et al. · 2021 · Nature Communications
  47. Multi-modal contrastive mutual learning and pseudo-label re-learning for semi-supervised medical image segmentation
    Shuo Zhang, Jiaojiao Zhang, Biao Tian, Thomas Lukasiewicz, Zhenghua Xu · 2022 · Medical Image Analysis
  48. Rapid Intraoperative Diagnosis of Pediatric Brain Tumors Using Stimulated Raman Histology
    Todd Charles Hollon, Spencer Lewis, Balaji Pandian, Yashar S. Niknafs, Mia R. Garrard, Hugh J. L. Garton, Cormac O. Maher, Kathryn A. McFadden, Matija Snuderl, Andrew P. Lieberman et al. · 2017 · Cancer Research
  49. Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Review
    Heather S. Haeberle, James Matthew Helm, Sergio Michael Navarro, Jaret M. Karnuta, Jonathan L. Schaffer, John J. Callaghan, Michael A. Mont, Atul F. Kamath, Viktor E. Krebs, Prem N. Ramkumar · 2019 · The Journal of Arthroplasty
  50. Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis
    Marya, Neil B, Powers, Patrick D, Chari, Suresh T, Gleeson, Ferga C, Leggett, Cadman L, Abu Dayyeh, Barham K, Chandrasekhara, Vinay, Iyer, Prasad G, Majumder, Shounak, Pearson, Randall K et al. · 2021 · Gut
  51. Deep learning-based data analytics for safety in construction
    Jiajing Liu, Hanbin Luo, Junxiao Liu · 2022 · Automation in Construction
  52. Novel research and future prospects of artificial intelligence in cancer diagnosis and treatment
    Zhang, Chaoyi, Xu, Jin, Tang, Rong, Yang, Jianhui, Wang, Wei, Yu, Xianjun, Shi, Si · 2023 · Journal of Hematology & Oncology
  53. Deep learning for detection of focal epileptiform discharges from scalp EEG recordings
    Marleen C. Tjepkema‐Cloostermans, Rafael C.V. de Carvalho, Michel J. A. M. van Putten · 2018 · Clinical Neurophysiology
  54. Lung Nodule Classification via Deep Transfer Learning in CT Lung Images
    Raul Victor M. da Nóbrega, Solon A. Peixoto, Suane Pires P. da Silva, Pedro P. Rebouças Filho · 2018 · Proceedings - IEEE Symposium on Computer-Based Medical Systems
  55. Deep learning how to fit an intravoxel incoherent motion model to diffusion‐weighted MRI
    Sebastiano Barbieri, Oliver J. Gurney‐Champion, Remy Klaassen, Harriet C. Thoeny · 2019 · Magnetic Resonance in Medicine
  56. Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning
    Milad Nasr, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, Nicholas Carlini · 2021 · IEEE Symposium on Security and Privacy (S&P)
  57. Integrating Artificial and Human Intelligence: A Partnership for Responsible Innovation in Biomedical Engineering and Medicine
    Kevin Dzobo, Sampson Kofi Adotey, Nicholas Ekow Thomford, Witness Dzobo · 2019 · OMICS A Journal of Integrative Biology
  58. Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images
    Luis R. Soenksen, Timothy Kassis, Susan Conover, Berta Martí-Fuster, Judith Birkenfeld, Jason M. Tucker-Schwartz, Asif Naseem, Robert R. Stavert, Caroline C. Kim, Maryanne Makredes Senna et al. · 2021 · Science Translational Medicine
  59. Toward Explainable Artificial Intelligence for Precision Pathology
    Frederick Klauschen, Jonas Dippel, Philipp Keyl, Philipp Sebastian Jurmeister, Michael Ludwig Bockmayr, Andreas Möck, Oliver Buchstab, Maximilian Alber, Lukas Ruff, Grégoire Montavon et al. · 2023 · Annual Review of Pathology Mechanisms of Disease
  60. An enhanced multimodal fusion deep learning neural network for lung cancer classification
    Sangeetha S.K.B, Sandeep Kumar Mathivanan, P. Karthikeyan, Hariharan Rajadurai, Basu Dev Shivahare, Saurav Mallik, Hong HQ Qin · 2023 · Systems and Soft Computing
  61. Detection of Flares by Decrease in Physical Activity, Collected Using Wearable Activity Trackers in Rheumatoid Arthritis or Axial Spondyloarthritis: An Application of Machine Learning Analyses in Rheumatology
    Gossec, Laure, Guyard, Frédéric, Leroy, Didier, Lafargue, Thomas, Seiler, Michel, Jacquemin, Charlotte, Molto, Anna, Sellam, Jérémie, Foltz, Violaine, Gandjbakhch, Frédérique et al. · 2019 · Arthritis Care & Research
  62. Generative models improve fairness of medical classifiers under distribution shifts
    Ktena, Ira, Wiles, Olivia, Albuquerque, Isabela, Rebuffi, Sylvestre-Alvise, Tanno, Ryutaro, Roy, Abhijit Guha, Azizi, Shekoofeh, Belgrave, Danielle, Kohli, Pushmeet, Cemgil, Taylan et al. · 2024 · Nature Medicine
  63. Biocompatible Batteries—Materials and Chemistry, Fabrication, Applications, and Future Prospects
    Sven Stauss, Itaru Honma · 2018 · Bulletin of the Chemical Society of Japan
  64. Computer-assisted diagnosis techniques (dermoscopy and spectroscopy-based) for diagnosing skin cancer in adults
    Lavinia Ferrante di Ruffano, Yemisi Takwoingi, Jacqueline Dinnes, Naomi Chuchu, Susan E Bayliss, Clare F Davenport, Rubeta Matin, Kathie Godfrey, Colette O'Sullivan, Abha Gulati et al. · 2018 · Cochrane Database of Systematic Reviews
  65. OrgaQuant: Human Intestinal Organoid Localization and Quantification Using Deep Convolutional Neural Networks
    Timothy Kassis, Victor Hernandez‐Gordillo, Ronit Langer, Linda Gay Griffith · 2019 · Scientific Reports
  66. Mean Field Analysis of Neural Networks: A Law of Large Numbers
    Justin A. Sirignano, Konstantinos Spiliopoulos · 2020 · SIAM Journal on Applied Mathematics
  67. Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging
    Matthew Li, Ken Chang, Benjamin Bearce, Connie Y. Chang, Ambrose J. Huang, J. Peter Campbell, James M. Brown, Praveer Singh, Katharina Hoebel, Deniz Erdogmus B et al. · 2020 · npj Digital Medicine
  68. Current Applications, Opportunities, and Limitations of AI for 3D Imaging in Dental Research and Practice
    Kuo Feng Hung, Andy Wai Kan Yeung, Ray Tanaka, Michael Marc Bornstein · 2020 · International Journal of Environmental Research and Public Health
  69. Identification of Melanoma From Hyperspectral Pathology Image Using 3D Convolutional Networks
    Qian Wang, Sun Li, Yan Wang, Mei Zhou, Menghan Hu, Jiangang Chen, Ying Wen, Qingli Li · 2020 · IEEE Transactions on Medical Imaging
  70. Smart Materials Enabled with Artificial Intelligence for Healthcare Wearables
    Youbin Zheng, Ning Tang, Rawan Omar, Zhipeng Hu, Tuan Duc Duong, Jing Wang, Weiwei Wu, Hossam Haick · 2021 · Advanced Functional Materials
  71. Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare
    Sarmad Maqsood, Robertas Damaševičius · 2023 · Neural Networks
  72. DeepHeart: Semi-Supervised Sequence Learning for Cardiovascular Risk Prediction
    Ballinger, Brandon, Hsieh, Johnson, Singh, Avesh, Sohoni, Nimit, Wang, Jack, Tison, Geoffrey, Marcus, Gregory, Sanchez, Jose, Maguire, Carol, Olgin, Jeffrey et al. · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
  73. Artificial intelligence applications in dermatology: Where do we stand?
    Gomolin, Arieh, Netchiporouk, Elena, Gniadecki, Robert, Litvinov, Ivan V. · 2020 · Frontiers in Medicine
  74. Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: Comparison with expert subjective assessment
    Christiansen, F., Epstein, E. L., Smedberg, E., Åkerlund, M., Smith, K., Epstein, E. · 2021 · Ultrasound in Obstetrics & Gynecology
  75. Comprehensive analysis of lung cancer pathology images to discover tumor shape and boundary features that predict survival outcome
    Shidan Wang, Alyssa Chen, Lin Yang, Ling Cai, Yang Xie, Junya Fujimoto, Adi F. Gazdar, Guanghua Xiao · 2018 · Scientific Reports
  76. Applications of Artificial Intelligence in Ophthalmology: General Overview
    Wei Lü, Yan Tong, Yue Yu, Yiqiao Xing, Changzheng Chen, Yin Shen · 2018 · Journal of Ophthalmology
  77. Challenges in Personalized Nutrition and Health
    Meghna Verma, Raquel Hontecillas, Nuria Tubau‐Juni, Vida Abedi, Josep Bassaganya-Riera · 2018 · Frontiers in Nutrition
  78. Optical coherence tomography for diagnosing skin cancer in adults
    Lavinia Ferrante di Ruffano, Jacqueline Dinnes, Jonathan James Deeks, Naomi Chuchu, Susan E Bayliss, Clare F Davenport, Yemisi Takwoingi, Kathie Godfrey, Colette O'Sullivan, Rubeta Matin et al. · 2018 · Cochrane Database of Systematic Reviews
  79. Towards Automated Melanoma Detection With Deep Learning: Data Purification and Augmentation
    Devansh Bisla, Anna Choromanska, Russell S. Berman, Jennifer Stein, David Polsky · 2019 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  80. Automated acquisition of explainable knowledge from unannotated histopathology images
    Yoichiro Yamamoto, Toyonori Tsuzuki, Jun Akatsuka, Masao Ueki, Hiromu Morikawa, Yasushi Numata, Taishi Takahara, Takuji Tsuyuki, Kotaro Tsutsumi, Ryuto Nakazawa et al. · 2019 · Nature Communications
  81. Detection of Cardiac Structural Abnormalities in Fetal Ultrasound Videos Using Deep Learning
    Masaaki Komatsu, Akira Sakai, Reina Komatsu, Ryu Matsuoka, Suguru Yasutomi, Kanto Shozu, Ai Dozen, Hidenori Machino, Hirokazu Hidaka, Tatsuya Arakaki et al. · 2021 · Applied Sciences
  82. AI for managing open innovation: Opportunities, challenges, and a research agenda
    Thijs Broekhuizen, Henri C. Dekker, Pedro de Faria, Sebastian Firk, Dinh Khoi Nguyen, Wolfgang Sofka · 2023 · Journal of Business Research
  83. Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review
    Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, Navid Ghassemi, Delaram Sadeghi, Parisa Moridian, Ali Akbar Khadem, Roohallah Alizadehsani, Sadiq Hussain, Assef Zare et al. · 2020 · arXiv (Cornell University)
  84. Human Factors Challenges for the Safe Use of Artificial Intelligence in Patient Care
    Sujan, Mark, Furniss, Dominic, Grundy, Kath, Grundy, Howard, Nelson, David, Elliott, Matthew, White, Sean, Habli, Ibrahim, Reynolds, Nick · 2019 · BMJ Health & Care Informatics
  85. Automated ICD-9 Coding via A Deep Learning Approach
    Min Li, Zhihui Fei, Min Zeng, Fang‐Xiang Wu, Yaohang Li, Yi Feng Pan, Jianxin Wang · 2018 · IEEE Transactions on Computational Biology and Bioinformatics
  86. Why imaging data alone is not enough: AI-based integration of imaging, omics, and clinical data
    Andreas Holzinger, Benjamin Haibe‐Kains, Igor Jurišica · 2019 · European Journal of Nuclear Medicine and Molecular Imaging
  87. Explainable skin lesion diagnosis using taxonomies
    Catarina Barata, M. Emre Celebi, Jorge Salvador Marques · 2020 · Pattern Recognition
  88. Soft Attention Improves Skin Cancer Classification Performance
    Soumyya Kanti Datta, Mohammad Abuzar Shaikh, Sargur N. Srihari, Mingchen Gao · 2021 · Lecture notes in computer science
  89. Deep learning with ultrasonography: automated classification of liver fibrosis using a deep convolutional neural network
    Lee, Jeong Hyun, Joo, Ijin, Kang, Tae Wook, Paik, Yong Han, Sinn, Dong Hyun, Ha, Sang Yun, Kim, Kyunga, Choi, Choonghwan, Lee, Gunwoo, Yi, Jonghyon et al. · 2020 · European Radiology
  90. AI-Powered Diagnosis of Skin Cancer: A Contemporary Review, Open Challenges and Future Research Directions
    Melarkode, Navneet, Srinivasan, Kathiravan, Qaisar, Saeed Mian, Plawiak, Pawel · 2023 · Cancers
  91. Improved Peptide Retention Time Prediction in Liquid Chromatography through Deep Learning
    Chunwei Ma, Yan Ren, Jiarui Yang, Zhe Ren, Huanming Yang, Siqi Liu · 2018 · Analytical Chemistry
  92. Cardiac tissue engineering: state-of-the-art methods and outlook
    Anh Hoa Nguyen, Paul Marsh, Lauren Schmiess-Heine, Peter John Burke, Abraham Phillip Lee, Juhyun Lee, Hung Cao · 2019 · Journal of Biological Engineering
  93. Deep learning of HIV field-based rapid tests
    Valérian Turbé, Carina Herbst, Thobeka Mngomezulu, Sepehr Meshkinfamfard, Nondumiso Dlamini, Thembani Mhlongo, Theresa K. Smit, Valeriia Cherepanova, Koki Shimada, Jobie Budd et al. · 2021 · Nature Medicine
  94. Multiclass Skin Lesion Classification Using a Novel Lightweight Deep Learning Framework for Smart Healthcare
    Long Hoang, Suk‐Hwan Lee, Eung-Joo Lee, Ki‐Ryong Kwon · 2022 · Applied Sciences
  95. Retinal Disease Detection Using Deep Learning Techniques: A Comprehensive Review
    Stewart Muchuchuti, Serestina Viriri · 2023 · Journal of Imaging
  96. The fundamentals of Artificial Intelligence in medical education research: AMEE Guide No. 156.
    Tolsgaard, Martin G., Pusic, Martin V., Sebok-Syer, Stefanie S., Gin, Brian, Svendsen, Morten Bo, Syer, Mark D., Brydges, Ryan, Cuddy, Monica M., Boscardin, Christy K. · 2023 · Medical Teacher
  97. Machine Learning Approaches in Cardiovascular Imaging
    Mir Henglin, Gillian Stein, Pavel V. Hushcha, Jasper Snoek, Alexander B. Wiltschko, Susan C. Cheng · 2017 · Circulation Cardiovascular Imaging
  98. Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning
    Varadarajan, Avinash V., Bavishi, Pinal, Ruamviboonsuk, Paisan, Chotcomwongse, Peranut, Venugopalan, Subhashini, Narayanaswamy, Arunachalam, Cuadros, Jorge, Kanai, Kuniyoshi, Bresnick, George, Tadarati, Mongkol et al. · 2020 · Nature Communications
  99. Diagnosis of skin diseases using Convolutional Neural Networks
    Jainesh Rathod, Vishal Waghmode, Aniruddh Sodha, Praseniit Bhavathankar · 2018 · International Conference on Electronics, Communication and Aerospace Technology (ICECA)
  100. Who Is Included in Human Perceptions of AI?: Trust and Perceived Fairness around Healthcare AI and Cultural Mistrust
    Lee, Min Kyung, Rich, Katherine · 2021 · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems