Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Vascular endothelial growth factor-A and drug level in serum and human breast milk of a lactating woman after intravitreal injection of ranibizumab: a case report. [PDF]
Zhang J +5 more
europepmc +1 more source
VEGF-A isoforms induce the expression of APLN in endothelial cells during human prenatal lung development. [PDF]
Hoarau A +7 more
europepmc +1 more source
Efficacy of a single dose switch from aflibercept to ranibizumab in the treatment of neovascular age-related macular degeneration. [PDF]
Iby J +6 more
europepmc +1 more source
Morphologic Changes of Macular Choroidal Neovascularization on OCT Angiography Following Faricimab Therapy in Patients With AMD. [PDF]
Loya A +4 more
europepmc +1 more source
Pharmacological Treatment for Diabetic Macular Edema: A 2025 Update on Durability and Multi-Target Therapies. [PDF]
Tao Y, Zhang Y, Xu W, Liu G, Liu H.
europepmc +1 more source
Correction for Waldeck-Weiermair et al., Dynamic regulation of receptor-modulated endothelial NADPH oxidases. [PDF]
europepmc +1 more source

