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Intelligent e-Tools for Wound Image Understanding and Evaluation

机译:智能电子工具用于伤口图像理解和评估

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This paper presents a Java framework for analyzing, processing and understanding wound images, to be used in teaching, learning and research activities. We intend to promote e-learning technologies in medical, pharmaceutical and health care domains. Using Java and XML technologies, we build models for various categories of wounds, due to various etiologies. Based on color and texture analysis, we identify the main barriers to wound healing, such as tissue nonviable, infection, inflammation, moisture imbalance, or edge non-advancing. This framework provides the infrastructure for preparing e-learning scenarios based on practice and real world experiences. We make experiments for wound healing simulation using various treatments and compare the results with experimental observations. Our experiments are supported by XML based databases containing knowledge extracted from previous wound healing experiences and from medical experts' knowledge. Also, we rely on new paradigms of the Artificial Intelligence for creating e-Iearning scenarios to be used in a context of active learning, for wound image understanding. To implement the e-learning tools, we use Java technologies for dynamic processes and XML technologies for dynamic content. Our approach to e-learning is so called blended learning, which combines traditional face-to-face and Web-based on-line learning, with focus on principles of active learning.
机译:本文介绍了用于分析,处理和理解伤口图像的Java框架,用于用于教学,学习和研究活动。我们打算促进医疗,制药和医疗保健领域的电子学习技术。使用Java和XML技术,由于各种病因,我们为各类伤口构建模型。基于颜色和纹理分析,我们识别伤口愈合的主要障碍,如组织不可行,感染,炎症,水分不平衡或边缘不前进。该框架为基于实践和现实世界经验提供了准备电子学习情景的基础设施。我们使用各种治疗进行伤口愈合模拟进行实验,并将结果与​​实验观察结果进行比较。我们的实验由基于XML的数据库支持,其中包含从先前的伤口治疗经验和医学专家知识中提取的知识。此外,我们依赖于人工智能的新范式,以创建在主动学习的背景下使用的电子IERING学习方案,以便伤害图像理解。要实现电子学习工具,我们将使用Java技术进行动态进程和XML技术进行动态内容。我们的电子学习方法如此称为混合学习,它将传统面对面和基于Web的在线学习结合在一起,重点是主动学习的原则。

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