Fig. 1: Workflow diagram showing the overview of developing deep learning systems to detect PM as well as myopic maculopathy. PM pathologic myopia, NPM none pathologic myopia, DLS deep learning system. *20 graders were randomly grouped into five teams with each team involving three general ophthal...
Development of deep learning architecture for automatic classification of outdoor mobile LiDAR dataThis paper proposes a deep convolutional neural network (CNN) architecture for automatic classification of mobile laser scanning (MLS) data obtained for outdoor environment, which are characterized by noise,...
Recently, artificial intelligence (AI) techniques, especially deep learning models, have made significant advance in big data feature learning. Human expert-level or even better achievements of deep learning have been reported in the screening and diagnosis of diseases with medical images13,14,15,16....
2018-Development and evaluation of a deep learning model for p–l binding affinity prediction NeedKnowledge AIDD,不积跬步 无以至千里 目录 收起 Abstract 1 Introduction 2 Materials and methods 2.1 Data 2.2 Network 5 Conclusions Abstract 动机:基于结构的配体发现是加速药物发现过程中最成功的方法之一...
【医学+深度论文:F13】2018 Development of a deep residual learning algorithm to screen for glaucoma from,程序员大本营,技术文章内容聚合第一站。
Importance: Non-contrast head CT scan is the current standard for initial imaging of patients with head trauma or stroke symptoms. Objective: To develop and validate a set of deep learning algorithms for automated detection of following key findings from non-contrast head CT scans: intracranial hem...
Deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior, removing the need to specify rules explicitly. Application of these methods to medical imaging requires further assessment and ...
Symbolizing communication and cooperation between the East and the West, the millennia-old silk routes demonstrated that by upholding solidarity and mutual trust, equality and mutual benefit, inclusiveness and mutual learning, and win-win cooperation, countries of different ethnic groups, beliefs and cu...
Here we report an interpretable deep learning strategy that delineates unique Alzheimer's disease signatures from multimodal inputs of MRI, age, gender, and Mini-Mental State Examination score. Our framework linked a fully convolutional network, which constructs high resolution maps of disease ...
Delaying intubation for patients failing Bi-Level Positive Airway Pressure (BIPAP) may be associated with harm. The objective of this study was to develop a deep learning model capable of aiding clinical decision making by predicting Bi-Level Positive Ai