https://github.com/artificialzeng/chip2019task3

第五届中国健康信息处理会议(CHIP2019)- 评测三:临床试验筛选标准短文本分类

https://github.com/artificialzeng/chip2019task3

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 4 DOI reference(s) in README
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (2.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

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第五届中国健康信息处理会议(CHIP2019)- 评测三:临床试验筛选标准短文本分类

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  • Host: GitHub
  • Owner: ArtificialZeng
  • Default Branch: main
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Fork of TJBioMedNLP/chip2019task3
Created over 5 years ago · Last pushed over 5 years ago

https://github.com/ArtificialZeng/chip2019task3/blob/main/

# --

- [](http://cips-chip.org.cn/)
- [](http://www.cips-chip.org.cn:8088/evaluation)

## 1.

> 
>



## 2.

44



| ID   | ()         | ()              |
| ---- | ---------------------- | ----------------------- |
| S1   | >80              | Age                     |
| S2   |  | Therapy or Surgery      |
| S3   | <2.7mmol/L         | Laboratory Examinations |

44

|#|group topics|semantic categories|
|---|---|----|
|1|`Health Status`|`Disease` `Symptom` `Sign` `Pregnancy-related Activity` `Neoplasm Status` `Non-Neoplasm Disease Stage` `Allergy Intolerance` `Organ or Tissue Status` `Life Expectancy` `Oral related`|
|2|`Treatment or Health Care`|`Pharmaceutical Substance or Drug` `Therapy or Surgery` `Device` `Nursing`|
|3|`Diagnostic or Lab Test`|`Diagnostic` `Laboratory Examinations` `Risk Assessment` `Receptor Status`|
|4|`Demographic Characteristics`|`Age` `Special Patient Characteristic` `Literacy` `Gender` `Education` `Address` `Ethnicity`|
|5|`Ethical Consideration`|`Consent` `Enrollment in other studies` `Researcher Decision` `Capacity` `Ethical Audit` `Compliance with Protocol`|
|6|`Lifestyle Choice`|`Addictive Behavior` `Bedtime` `Exercise` `Diet` `Alcohol Consumer` `Sexual related` `Smoking Status` `Blood Donation`|
|7|`Data or Patient Source`|`Encounter` `Disabilities` `Healthy` `Data Accessible`|
|8|`Other`|`Multiple`|

## 3.

#### 

		train_data.txt22962

#### 

		validation_data.txt7682

#### 

		test_data.txt7697

#### 

		chip2019task3_evaluation.py

		 

```
python chip2019task3_evaluation.py ./example_gold.txt ./example_pred.txt
```


#### 

		category.xlsx44

## 4.

27

- 


|    |    |    |    |    |
| ---------- | -------- | -------- | -------- | -------- |
| Average F1 | 0.810263 | 0.553736 | 0.770502 | 0.788728 |

- 


| **** | ****                   | ****                                                 | ****    | **F1** |
| -------- | ------------------------------ | ------------------------------------------------------------ | ----------------- | -------------- |
| 1        |                    |  |                 | 0.810 263      |
| 2        |                    |  | www.chictr.org.cn | 0.809 936      |
| 3        |                    |  |                 | 0.807 456      |
| 4        |                        |                                          |                 | 0.800 168      |
| 5        |    |                                          |                 | 0.800 123      |
| 6        |        |  |                 | 0.797 970      |
| 7        |                        |  |                 | 0.796 295      |
| 8        |                        | +- |                 | 0.795 773      |
| 9        |                        |                                          |                 | 0.794 909      |

- 


|  |      |  |                                        |  |
| ---- | ------------ | -------- | ---------------------------------------------- | ------ |
| 1    |  | wzm      | BERT             |  |
| 2    |  | DUTIR914 |          |  |
| 3    |  | DUTIRTM  | BERT |  |

- 


| **** | ****                    | **** | ****                             | ****                                   |
| -------- | ------------------------------- | ------------ | ------------------------------------ | ---------------------------------------------- |
| 4        |                         |      |                        |  |
| 5        |     |  |                          | BERT           |
| 6        |         | mini batch   |  |  |
| 7        |                         | Morning Tea  |                    |  |
| 8        |                         | zzunlp       |                          |                      |
| 9        |                         | A&D          |           | ERNIE                            |

## 5.

, , , , , , . . , 2021, 38(1): 105-110, 121. doi: 10.7507/1001-5515.202006035

## 6.



****

```
@article{
  title={},
  author={,,,,,,},
  journal={},
  year={2021},
  doi={10.7507/1001-5515.202006035}
}
```

****

```
@article{
  title={},
  author={,,,,,,,},
  journal={()},
  year={2020},
  doi={10.13451/j.sxu.ns.2020084}
}
```

****

```
@article{
  title={An Ensemble Learning Strategy for Eligibility Criteria Text Classification for Clinical Trial Recruitment: Algorithm Development and Validation},
  author={Kun Zeng, Zhiwei Pan, Yibin Xu, Yingying Qu},
  journal={JMIR Medical Informatics},
  year={2020},
  doi={10.2196/17832}
}
```

## 7.

- zonghui@tongji.edu.cn
- 
- zuo.feng.li@philips.com
- 

Owner

  • Name: Dr. Artificial曾小健
  • Login: ArtificialZeng
  • Kind: user
  • Location: Beijing

LLM practitioner/engineer, AI/ML/DL Quant

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