🚀 生物醫學命名實體識別模型
這是一個英文命名實體識別模型,可從給定文本語料(如病例報告)中識別生物醫學實體(共107種實體),為生物醫學領域的信息提取提供了有力支持。
🚀 快速開始
本模型可以通過從Hugging Face加載推理API,或者使用transformers
庫提供的pipeline
對象這兩種方式使用。
✨ 主要特性
- 實體識別能力:能夠識別107種生物醫學實體,適用於病例報告等文本語料。
- 模型基礎:基於
distilbert-base-uncased
構建。
- 訓練數據集:使用Maccrobat數據集進行訓練,數據集鏈接:https://figshare.com/articles/dataset/MACCROBAT2018/9764942 。
- 碳排放:訓練過程中的碳排放為0.0279399890043426千克。
- 訓練時間:訓練耗時30.16527分鐘。
- 使用的GPU:1 x GeForce RTX 3060 Laptop GPU。
💻 使用示例
基礎用法
from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("d4data/biomedical-ner-all")
model = AutoModelForTokenClassification.from_pretrained("d4data/biomedical-ner-all")
pipe = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="simple")
pipe("""The patient reported no recurrence of palpitations at follow-up 6 months after the ablation.""")
📚 詳細文檔
查看本模型及相應Python庫的講解教程視頻:https://youtu.be/xpiDPdBpS18
📄 許可證
本模型採用Apache-2.0許可證。
👨🔬 作者信息
本模型是Deepak John Reji和Shaina Raza開展的“生物醫學領域的人工智能”研究課題的一部分。如果您使用了本項目的代碼、模型或數據集,請在以下倉庫點星支持:
https://github.com/dreji18/Bio-Epidemiology-NER
💗 支持作者
如果您想支持作者,可以點擊下面的按鈕請作者喝咖啡:

測試樣例
以下是一些測試用的文本樣例:
CASE: A 28-year-old previously healthy man presented with a 6-week history of palpitations.
The symptoms occurred during rest, 2–3 times per week, lasted up to 30 minutes at a time and were associated with dyspnea.
Except for a grade 2/6 holosystolic tricuspid regurgitation murmur (best heard at the left sternal border with inspiratory accentuation), physical examination yielded unremarkable findings.
A 63-year-old woman with no known cardiac history presented with a sudden onset of dyspnea requiring intubation and ventilatory support out of hospital.
She denied preceding symptoms of chest discomfort, palpitations, syncope or infection.
The patient was afebrile and normotensive, with a sinus tachycardia of 140 beats/min.
A 48 year-old female presented with vaginal bleeding and abnormal Pap smears.
Upon diagnosis of invasive non-keratinizing SCC of the cervix, she underwent a radical hysterectomy with salpingo-oophorectomy which demonstrated positive spread to the pelvic lymph nodes and the parametrium.
Pathological examination revealed that the tumour also extensively involved the lower uterine segment.