electricsheepafrica/Africa-Cerebral-palsy-synthetic-dataset

非洲脑瘫合成数据集是一套为非洲人群脑瘫检测设计的合成数据集，使用文献信息概率建模生成。该数据集旨在解决非洲地区现实世界数据收集的挑战，包括资源限制、诊断延迟和类别不平衡。数据集包含区域特定的风险因素和流行病学模式，旨在用于算法原型开发、资助申请和建立现实世界验证的基线。它由九个具有不同配置的数据集组成，用于算法开发，并且详细描述了生成合成数据的方法论，包括概率采样框架、非洲人口参数、脑瘫概率模型、脑瘫分类和特征集。README还提供了模型训练协议、评估指标、预期结果、局限性、数据集适当使用的指导。它还提供了关于可重复性、引用、代码可用性和联系支持的信息。

The African Cerebral Palsy Synthetic Dataset is a suite of synthetic datasets designed for the detection of cerebral palsy (CP) in African populations, generated using literature-informed probabilistic modeling. It addresses challenges in real-world data collection in Africa, such as resource constraints, diagnostic delays, and class imbalance, by incorporating region-specific risk factors and epidemiological patterns. The dataset is intended for algorithm prototyping, grant applications, and establishing baselines for real-world validation. It consists of nine datasets with varied configurations for algorithm development, and the methodology for generating the synthetic data is described in detail, including the probabilistic sampling framework, African population parameters, CP probability model, CP classification, and feature set. The README also provides guidance on model training protocols, evaluation metrics, expected outcomes, limitations, and appropriate use of the dataset. It concludes with information on reproducibility, citation, code availability, and contact for support.