白血病专病数据集

电子病历文本细项解析方法：首先对于病历文本数据，进行分层解析，将获取到的文本数据按事件流的方式进行拆解，根据需要解析的各项信息，有针对性的选取包含该信息的内容类别事件流，进一步行各项指标的细项结构化解析。
专病诊断名称分类模型：通过分析医学文献、临床数据和专家知识，建立一个诊断数据库。经过分词和打乱顺序的预处理后，使用 train_supervised 函数进行训练（迭代200次，学习率0.1，词N-grams长度为1，损失函数为"hs"）。模型性能通过 classification_report 方法评估，表现良好。参数更新通过命令同步模型、标签和标签名，从而快速、准确地诊断专病类型。

Method for Fine-grained Parsing of Electronic Medical Record Text: First, hierarchical parsing is conducted on medical record text data. The acquired text data is decomposed into event streams. For each specific information item requiring parsing, the event streams of content categories containing the target information are selectively selected, followed by further fine-grained structured parsing of various indicators.

Specialized Disease Diagnosis Name Classification Model: A diagnostic database is established by analyzing medical literature, clinical data and expert knowledge. After preprocessing steps including word segmentation and random shuffling, the `train_supervised` function is employed for training with parameters set as 200 iterations, learning rate of 0.1, word N-grams length of 1, and loss function set to "hs". The model's performance is evaluated using the `classification_report` method, which demonstrates good results. Parameter updates are synchronized with the model, labels and label names via commands, enabling fast and accurate diagnosis of specialized disease types.

搜集汇总

数据集介绍

特点

白血病专病数据集由天津健康医疗大数据有限公司提供，包含26万条数据，每月更新。数据集涵盖白血病患者的临床特征、治疗模式等信息，适用于医疗、教学和科研领域，为医疗政策制定和资源分配提供依据。