Table_2_Predicting 24-hour intraocular pressure peaks and averages with machine learning.DOCX

Purpose<p>Predicting 24-hour peak and average intraocular pressure (IOP) is essential for the diagnosis and management of glaucoma. This study aimed to develop and assess a machine learning model for predicting 24-hour peak and average IOP, leveraging advanced techniques to enhance prediction...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Ranran Chen (3308463) (author)
مؤلفون آخرون:	Jinming Lei (17911294) (author), Yujie Liao (11413328) (author), Yiping Jin (15149721) (author), Xue Wang (102830) (author), Xiaomei Li (502923) (author), Danping Wu (9624389) (author), Hong Li (20183) (author), Yanlong Bi (7499644) (author), Haohao Zhu (6540695) (author)
منشور في:	2024
الموضوعات:	Dermatology Emergency Medicine Gastroenterology and Hepatology Geriatrics and Gerontology Intensive Care Medical Genetics (excl. Cancer Genetics) Nephrology and Urology Nuclear Medicine Orthopaedics Otorhinolaryngology Pathology (excl. Oral Pathology) Radiology and Organ Imaging Foetal Development and Medicine Obstetrics and Gynaecology Family Care Primary Health Care Medical and Health Sciences not elsewhere classified intraocular pressure 24-hour measurement nocturnal machine learning glaucoma
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Table_2_Predicting 24-hour intraocular pressure peaks and averages with machine learning.DOCX

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