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57. Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review

63. Big Data

67. The knowledge mobilisation problem within horticulture in England between scientific based and grower based organisations

74. Under the Lens: Team Perception of Trauma Video Review

75. Direct head-to-head comparison of convolutional long short-term memory and transformer networks for artificial Intelligence-based quantification of atherosclerotic plaque and stenosis from coronary CT angiography

82. Supplementary Table 1 from Glomus Tumors in Neurofibromatosis Type 1: Genetic, Functional, and Clinical Evidence of a Novel Association

83. Data from Glomus Tumors in Neurofibromatosis Type 1: Genetic, Functional, and Clinical Evidence of a Novel Association

84. Supplementary Table 2 from Glomus Tumors in Neurofibromatosis Type 1: Genetic, Functional, and Clinical Evidence of a Novel Association

85. Supplementary Figure Legend from Glomus Tumors in Neurofibromatosis Type 1: Genetic, Functional, and Clinical Evidence of a Novel Association

86. Supplementary Figure 1 from Glomus Tumors in Neurofibromatosis Type 1: Genetic, Functional, and Clinical Evidence of a Novel Association

93. Changes in insulin resistance following antidepressant treatment mediate response in major depressive disorder

97. 1.30 The Distinction Between Social Connectedness and Support When Examining Depression Among Children and Youth During the COVID-19 Pandemic

98. Creative Clinical Teaching in the Health Professions

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