Yongying Liu
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile
Get in touch with Yongying
Contact Yongying, search articles and posts on X, monitor coverage, and track replies from one place.
Learn more about Muck RackActions
Is this you?
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.Articles
Predicting Ki-67 expression levels in non-small cell lung cancer using an explainable CT-based deep learning radiomics model
1 Introductions Non-small cell lung cancer (NSCLC) is the most common pathological type of lung cancer and is associated with a relatively low average five-year survival rate (1–4). This clinical reality highlights the urgent need for improved prognostic assessment. Therefore, Ki-67, a validated indicator of tumor cell proliferation, has gained significant attention (5).
MiR-5195-3p functions as a tumor suppressor by targeting RHBDD1 in ovarian cancer
Zhanyu Wang [1] ; Xiaoping Zhang [1] ; Yongying Liu [1] ; Xiaoyan Shi [1] ; Lijun Li [1] ; Yun Jia [1] ; Fangfang Wu [1] ; Haosen Cui [1] ; Liang Li [1] [1] Fuyang Hospital of Anhui Medical University, Fuyang, Anhui Province, China Localización: Histology and histopathology: cellular and molecular biology, ISSN 0213-3911, ISSN-e 1699-5848, Vol. 38, Nº. 12, 2023, págs. 1403-1413 Idioma: inglés Enlaces Texto completo Resumen Background.
Actions
Is this you?
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.Get in touch with Yongying
Contact Yongying, search articles and posts on X, monitor coverage, and track replies from one place.
Learn more about Muck Rack