Distilbart Med Summary

🚀 醫療摘要生成與BART

本項目採用DistilBART模型，可根據輸入文本生成醫療摘要。該模型經過訓練，能夠理解醫療數據並生成簡潔且信息豐富的摘要。

🚀 快速開始

安裝依賴

若要使用該模型進行醫療摘要生成，請按以下步驟操作： 安裝所需的依賴項：

• pip install transformers
• pip install torch
• pip install datasets

代碼示例

from transformers import pipeline
summarizer = pipeline("summarization", model="Mahalingam/DistilBart-Med-Summary")

conversation = '''write the below JSON into normal text
{
  "Sex": "M",
  "ID": 585248,
  "DateOfBirth": "08/10/1995",
  "Age": "28 years",
  "VisitDate": "09/25/2023",
  "LogNumber": 6418481,
  "Historian": "Self",
  "TriageNotes": ["fever"],
  "HistoryOfPresentIllness": {
    "Complaint": [
      "The patient presents with a chief complaint of chills.",
      "The problem is made better by exercise and rest.",
      "The patient also reports change in appetite and chest pain/pressure as abnormal symptoms related to the complaint."
    ]
  }
}                                           
'''
nlp(conversation)

✨ 主要特性

DistilBART醫療摘要生成器基於Hugging Face深度學習容器構建，旨在根據輸入文本生成醫療摘要。本README提供瞭如何使用該模型的信息、架構細節以及下載途徑。

📚 詳細文檔

模型信息

📄 聯繫方式

若您對該模型有任何疑問或需要支持，請隨時聯繫：

• 姓名：Mahalingam Balasubramanian
• 郵箱：mahalingamb.1978@gmail.com