Canon Medical / RAEng Senior Research Fellow in Healthcare AI

Computer Science

1. Adversarial Machine Learning 14%
2. Algorithmic Bias 7%
3. And-States 14%
4. Annotation 100%
5. Appearance Characteristic 7%
6. Application Domain 7%
7. Approximation (Algorithm) 14%
8. Art Performance 7%
9. Artificial Intelligence 19%
10. Attention (Machine Learning) 11%
11. Automatic Machine 14%
12. Bidirectional Encoder Representations From Transformers 14%
13. Big Data 14%
14. Building-Blocks 14%
15. Classification Performance 18%
16. Classification Task 11%
17. Compositional Structure 7%
18. Computational Method 14%
19. Computer Vision 16%
20. Computer Vision Applications 14%
21. Continuous Variable 18%
22. Data Augmentation 7%
23. Data Privacy 7%
24. Dataset Source 14%
25. Deep Learning Method 28%
26. Deep Learning Model 33%
27. Deep Neural Network 7%
28. Developing Model 7%
29. Diagnostic Accuracy 7%
30. Difference Image 14%
31. Diffusion Model 28%
32. Directed Acyclic Graph 14%
33. Discriminator 14%
34. Disease Condition 7%
35. Distributionally Robust Optimization 14%
36. Domain Adaptation 14%
37. Experimental Result 14%
38. External Entity 7%
39. Generalizability 14%
40. Generalization Ability 18%
41. Generalization Performance 8%
42. Generative Model 28%
43. Image Analysis 40%
44. Image Classification 14%
45. Image Reconstruction 15%
46. Image Segmentation 81%
47. Image Sequence 14%
48. Image Synthesis 28%
49. Individual Level 14%
50. Information Present 7%
51. Input Processing 7%
52. Joint Distribution 18%
53. Knowledge Distillation 14%
54. Label Distribution 14%
55. Learned Feature 7%
56. Learning Ability 7%
57. Learning Approach 10%
58. Learning System 47%
59. Lesion Segmentation 14%
60. Level Heterogeneity 14%
61. Log Data 14%
62. Longitudinal Data 14%
63. Lower Performance 7%
64. Machine Learning 47%
65. Medical Diagnosis 7%
66. Medical Facility 7%
67. Medical Imaging 31%
68. Medical Practice 14%
69. Meta-Learning 14%
70. Multimodality 7%
71. Neural Network 28%
72. Neural Network Model 7%
73. Observational Data 14%
74. Optimization Space 14%
75. Optimization Technique 7%
76. Patient Information 7%
77. Performance Model 9%
78. Personal Information 14%
79. Phase Difference 7%
80. Population Level 14%
81. Postprocessing Method 7%
82. Process Synthesis 14%
83. Regularization 7%
84. Representation Learning 42%
85. Scientific Progress 7%
86. Sectional Data 9%
87. segmentation accuracy 11%
88. Segmentation Model 11%
89. Segmentation Performance 9%
90. Segmentation Task 7%
91. Semisupervised Learning 15%
92. Semisupervised Model 14%
93. Sensitive Attribute 7%
94. Sensitive Domain 7%
95. Shared Information 7%
96. Signal Intensity 14%
97. Subject Identity 18%
98. Substantial Amount 7%
99. Supervised Learning 10%
100. Surrounding Tissue 14%
101. Training Data 36%
102. Training Dataset 7%
103. Training Model 14%
104. Transformer Network 35%
105. Tumor Detection 14%
106. Tumor Segmentation 28%
107. Tuning Phase 7%
108. U-Net 17%
109. Unlabeled Data 7%
110. Widespread Adoption 14%