Crohn's Disease Treatment Prediction Model
收藏DataCite Commons2024-07-12 更新2024-07-13 收录
下载链接：
https://data.mendeley.com/datasets/y2hhsygy49/1
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资源简介：
DB for Machine learning using clinical data at baselines. Used to predicts the medium-term efficacy of biologic therapies for in patients with Crohn's Disease.
1. Data Collection Sources
- Electronic Health Records (EHR)
- Clinical trials and studies
- Genetic data
- Patient-reported outcomes
- Medical imaging
Types of Data
- Demographic information
- Clinical data (symptoms, disease severity, treatment history)
- Genetic data (SNPs, mutations)
- Lab results (CRP levels, fecal calprotectin)
- Imaging data (MRI, endoscopy)
- Lifestyle data (diet, smoking status)
2. Data Preprocessing Steps
- **Data Cleaning**: Handle missing values, remove duplicates, correct errors.
- **Data Normalization/Standardization**: Normalize lab results, standardize imaging data.
- **Feature Engineering**: Create new features from existing data, e.g., calculate disease activity scores.
- **Encoding Categorical Data**: Convert categorical variables to numerical ones using one-hot encoding or label encoding.
- **Data Splitting**: Split data into training, validation, and test sets.
提供机构：
Mendeley Data
创建时间：
2024-07-10
