最近參與了幾個臨床醫學課題，總結一下如何跨界結合

1： 確定研究的方向： 這個是決定文章的核心

       研究方向的時候，就要確定要投的期刊，平時看論文的時候要把一些常用的術語記錄下來，

       投的期刊，研究內容，方法記錄一下。

 

2：  研究團隊團隊搭建（負責人：負責讀論文,研究點 ,確定方案 

                                        程序員：負責代碼實現）

3：  定期的項目推進,復盤

如下是遇到的問題，Research Gate 討論交流過程

Study Summary 
This study aims to develop a machine learning model for personalized prediction of overall survival (OS) in lymphoma patients using retrospective data. The model incorporates input features such as survival time, treatment regimens, demographic characteristics, and laboratory test results to predict a binary outcome (alive vs. deceased). Once trained, the model is intended for clinical use, where patient-specific features (including dynamically adjusted survival time) are input to generate real-time survival probability estimates.  
Key Methodological Questions 
1. Modeling Approach 
   - Is using survival/death as a binary outcome while also including survival time as an input feature the optimal strategy?  
   - How should censored patients (e.g., lost to follow-up) be handled in this framework?  
2. Treatment-Related Features 
   - Can treatment-related variables (e.g., specific regimens) be legiti