ACM Grand Challenge 2020 BioMedia
The first two tasks relate to predicting common measurements used for semen quality assessment, For both tasks, participants are asked to perform video analysis over single frame analysis.
- motility: predict the percentage of progressive, non-progressive, and immotile sperm in a given video sample.
- morphology: predict the percentage of sperm with head defects, midpiece defects, and tail defects.
https://github.com/simula/biomedia-2020/wiki/Dataset
VISEM contains five CSV files:
semen_analysis_data.csv: The results of standard semen analysis(标准精液分析).
fatty_acids_spermatozoa.csv: The levels of several fatty acids in the spermatozoa of the participants(几种脂肪酸水平).
fatty_acids_serum.csv: The serum levels of the fatty acids of the phospholipids (measured from the blood of the participant)(磷脂脂肪酸水平).
sex_hormones.csv: The serum levels of sex hormones measured in the blood of the participants(性激素水平).
study_participant_related_data.csv: General information about the participants such as age, abstinence time and Body Mass Index (BMI)(参与者一般信息：年龄、禁欲时间和体重指数等).
videos.csv: Overview of which video-file belongs to what participants(哪个视频文件属于哪些参与者).
Mean squared error, mean absolute error and the root mean squared error.
sklearn: 0.21.2
lightgbm: 2.2.3
xgboost: 1.1.1
Motility
| Task | Mae | Mse | Rmse |
|---|---|---|---|
| Non-progressive sperm motility | 6.99754 | 81.37438 | 8.92189 |
| Progressive motility | 10.34852 | 171.49138 | 13.06471 |
| Immotile sperm | 8.56650 | 180.13383 | 13.38379 |
| Mean | 8.63752 | 144.33320 | 11.79013 |
Morphology
| Task | Mae | Mse | Rmse |
|---|---|---|---|
| Head defects | 1.45439 | 4.15771 | 2.03593 |
| Midpiece and neck defects | 7.78641 | 92.97207 | 9.63498 |
| Tail defects | 5.43461 | 66.92127 | 8.14526 |
| Mean | 4.89180 | 54.68368 | 6.60539 |