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Machine learn for glaucoma
Machine learn for glaucoma
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Harvard Dataverse
2018-11-15 更新
2026-04-09 收录
青光眼诊断
医疗机器学习
数据链接:
https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/1YRRAC
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资源简介:
Machine learn for glaucoma
应用场景:
提供机构:
Kim
创建时间:
2018-01-01
相关数据集
Study ophthalmic examinations.
青光眼诊断
眼科检查参数
Legend: VCDR = vertical cup-to-disc ratio, HCDR = horizontal cup-to-disc ratio, IOP = intraocular pressure, FDT = frequency doubling technology, CCT = central corneal thickness, HRT = Heid
NIAID Data Ecosystem
3
0
Machine learning for identifying risk of death in patients with severe fever with thrombocytopenia syndrome
死亡风险预测
医疗机器学习
Raw data of the manuscript
NIAID Data Ecosystem
3
0
Comparison of peripapillary retinal nerve fiber layer thickness between horizontal and vertical scan settings in different sectors.
OCT光学相干断层扫描
青光眼诊断
Comparison of peripapillary retinal nerve fiber layer thickness between horizontal and vertical scan settings in different sectors.
NIAID Data Ecosystem
2
0
Machine learn for glaucoma
青光眼辅助诊断
医疗机器学习
Machine learn for glaucoma
NIAID Data Ecosystem
3
0
Additional file 4 of First observation of secondary childhood glaucoma in Coffin-Siris syndrome: a case report and literature review
罕见病临床表型
青光眼诊断
Additional file 4. Comparison of clinical features in aniridia, Peters anomaly, and this patient. ✓ = present. n.k. = not known due to corneal opacity.
Figshare
2021-01-26 更新
3
0
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