ClarusC64/clinical-fluid-balance-instability-v0.1

该数据集用于评估模型是否能检测液体平衡动态中的不稳定性。每个数据行代表一个简化的临床液体管理场景，观察三个时间点。任务目标是判断系统是否保持体积稳定或趋向液体过载不稳定性。数据集测试了多个方面的交互推理，包括液体输入轨迹、尿液输出轨迹、体重代理轨迹、肺液体标记轨迹、肾功能代理、利尿剂反应和干预延迟。预测目标为标签1表示液体平衡不稳定性，标签0表示稳定的体积轨迹。数据集的评估指标包括准确率、精确率、召回率、F1分数和混淆矩阵。

This dataset evaluates whether models can detect instability in fluid balance dynamics. Each row represents a simplified clinical fluid-management scenario observed across three time points. The task is to determine whether the system remains volume-stable or is moving toward fluid overload instability. The dataset tests interaction reasoning across: fluid input trajectory, urine output trajectory, body weight proxy trajectory, lung fluid marker trajectory, renal function proxy, diuretic response, and intervention delay. The prediction target is label = 1 for fluid balance instability and label = 0 for stable volume trajectory. The evaluation metrics include accuracy, precision, recall, f1, and confusion matrix.