Dermatologist-level classification of skin cancer with deep neural networks

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2. Cognitive Challenges in Human-Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation
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3. Ethics and governance of trustworthy medical artificial intelligence
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4. Evaluate the Malignancy of Pulmonary Nodules Using the 3-D Deep Leaky Noisy-OR Network
   Fangzhou Liao, Ming Liang, Zhe Li, Xiaolin Hu, Sen Song · 2019 · IEEE Transactions on Neural Networks and Learning Systems
5. Leveraging uncertainty information from deep neural networks for disease detection
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6. Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy
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7. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
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8. Global evolution of research in artificial intelligence in health and medicine: a bibliometric study
   Tran, Bach Xuan, Vu, Giang Thu, Ha, Giang Hai, Vuong, Quan-Hoang, Ho, Manh-Tung, Vuong, Thu-Trang, La, Viet-Phuong, Ho, Manh-Toan, Nghiem, Kien-Cuong P., Nguyen, Huong Lan Thi et al. · 2019 · Journal of Clinical Medicine
9. Deep Learning in Medicine—Promise, Progress, and Challenges
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10. Backpropagation algorithms and Reservoir Computing in Recurrent Neural Networks for the forecasting of complex spatiotemporal dynamics
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11. An anatomization on breast cancer detection and diagnosis employing multi-layer perceptron neural network (MLP) and Convolutional neural network (CNN)
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12. Multi-class Arrhythmia detection from 12-lead varied-length ECG using Attention-based Time-Incremental Convolutional Neural Network
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13. Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks
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14. Opening the black box: interpretable machine learning for geneticists
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15. Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization
    Pegah Khosravi, Ehsan Mohamad Kazemi, Qiansheng Zhan, Jonas E. Malmsten, Marco Toschi, Pantelis Zisimopoulos, Alexandros Sigaras, Stuart A. Lavery, Lee Cooper, Cristina Fontes Lindemann Hickman et al. · 2019 · npj Digital Medicine
16. Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs
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17. Automated deep-neural-network surveillance of cranial images for acute neurologic events
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18. Self-supervised learning for medical image classification: a systematic review and implementation guidelines
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19. Artificial intelligence in medical education
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20. The future of early cancer detection
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21. Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI
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22. Automated detection and classification of the proximal humerus fracture by using deep learning algorithm
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23. Artificial intelligence in clinical and genomic diagnostics
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24. A review of deep learning with special emphasis on architectures, applications and recent trends
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25. Machine learning: applications of artificial intelligence to imaging and diagnosis
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26. Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension
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27. Automated Gleason grading of prostate cancer tissue microarrays via deep learning
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28. Artificial intelligence and machine learning for medical imaging: A technology review
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30. An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets
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31. Clinical applications of machine learning algorithms: beyond the black box
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32. Explainable Deep Learning: A Field Guide for the Uninitiated
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33. Artificial intelligence as the next step towards precision pathology
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34. Development and Validation of a Deep Learning–Based Automated Detection Algorithm for Major Thoracic Diseases on Chest Radiographs
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35. Artificial intelligence in histopathology: enhancing cancer research and clinical oncology
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36. Artificial intelligence in medicine: current trends and future possibilities
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37. Accumulation of cholesterol with age in human Bruch's membrane.
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38. Artificial intelligence: Implications for the future of work
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39. Skin lesion classification with ensembles of deep convolutional neural networks
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40. Deep learning for cardiovascular medicine: a practical primer
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41. Diagnosis of Pneumonia from Chest X-Ray Images Using Deep Learning
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42. Emerging role of deep learning‐based artificial intelligence in tumor pathology
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43. Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery
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44. Transparency and trust in artificial intelligence systems
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45. Optimizing Chemical Reactions with Deep Reinforcement Learning
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46. Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning
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47. Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans
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48. Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation
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49. RETRACTED ARTICLE: Artificial intelligence and machine learning in precision and genomic medicine
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50. Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study
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51. Deep neural network with generative adversarial networks pre-training for brain tumor classification based on MR images
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52. Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review
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53. Artificial intelligence-based image classification methods for diagnosis of skin cancer: Challenges and opportunities
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54. Cancer Diagnosis Using Deep Learning: A Bibliographic Review
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55. Deep neural networks are superior to dermatologists in melanoma image classification
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56. A convolutional neural network for sleep stage scoring from raw single-channel EEG
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57. Towards Generalist Biomedical AI
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58. Disc-Aware Ensemble Network for Glaucoma Screening From Fundus Image
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59. Can AI Help Reduce Disparities in General Medical and Mental Health Care?
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60. Artificial intelligence and the implementation challenge
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61. Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic study
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62. Convolutional neural networks for medical image analysis: State-of-the-art, comparisons, improvement and perspectives
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63. Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review
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64. Neural network analysis of sleep stages enables efficient diagnosis of narcolepsy
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65. An enhanced technique of skin cancer classification using deep convolutional neural network with transfer learning models
    Ali, Md Shahin, Miah, Md Sipon, Haque, Jahurul, Rahman, Md Mahbubur, Islam, Md Khairul · 2021 · Machine Learning with Applications
66. Skin Lesions Classification Into Eight Classes for ISIC 2019 Using Deep Convolutional Neural Network and Transfer Learning
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67. Hidden stratification causes clinically meaningful failures in machine learning for medical imaging
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68. AI in Health: State of the Art, Challenges, and Future Directions
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69. Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning
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70. Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms
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71. Improving health literacy using the power of digital communications to achieve better health outcomes for patients and practitioners.
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72. Why ResNet Works? Residuals Generalize
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73. Role of artificial intelligence in patient safety outcomes: systematic literature review
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74. Does Machine Translation Affect International Trade? Evidence from a Large Digital Platform
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75. The Application of Medical Artificial Intelligence Technology in Rural Areas of Developing Countries
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76. Measuring the Quality of Explanations: The System Causability Scale (SCS): Comparing Human and Machine Explanations
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77. Shifting machine learning for healthcare from development to deployment and from models to data
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78. The skin cancer classification using deep convolutional neural network
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79. Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms: A Scoping Review
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80. Deep Learning for Medical Anomaly Detection – A Survey
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81. Deep-chest: Multi-classification deep learning model for diagnosing COVID-19, pneumonia, and lung cancer chest diseases
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82. Artificial intelligence (AI) and big data in cancer and precision oncology
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83. Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study
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84. Artificial intelligence in oncology
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85. Medical image classification using synergic deep learning
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86. Deep Learning Models for Histopathological Classification of Gastric and Colonic Epithelial Tumours
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87. Advanced machine learning in action: identification of intracranial hemorrhage on computed tomography scans of the head with clinical workflow integration
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88. Artificial Intelligence–Based Breast Cancer Nodal Metastasis Detection: Insights Into the Black Box for Pathologists
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89. Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging
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90. Personalized Medicine and the Power of Electronic Health Records
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91. Deep learning in bioinformatics: Introduction, application, and perspective in the big data era
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93. Artificial Intelligence for Intraoperative Guidance
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94. Deep machine learning provides state-of-the-art performance in image-based plant phenotyping
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95. The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review
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96. State-of-the-Art Deep Learning in Cardiovascular Image Analysis
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97. Application of deep learning techniques for detection of COVID-19 cases using chest X-ray images: A comprehensive study
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98. Physician Confidence in Artificial Intelligence: An Online Mobile Survey
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99. The dark sides of artificial intelligence: An integrated AI governance framework for public administration
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100. Deep Learning for the Radiographic Detection of Apical Lesions
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