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
Exploring Health Care Providers, Families and Educators' Perceptions of an Online Self-Paced F-Words for Child Development Foundations Course. [PDF]
Canlas K +8 more
europepmc +1 more source
Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare
Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu +10 more
wiley +1 more source
Automatic generation and transfer of Yongju opera language using AIGC technology and style mapping. [PDF]
Meng X, Hu P, Li Z.
europepmc +1 more source
Generative AI‐Driven Accelerated Discovery of Passivation Molecules for Perovskite Solar Cells
A generative artificial intelligence (AI) framework combining a discriminative machine learning model (SMILES‐X) and a generative language model (GPT‐2) autonomously discovers new molecular passivators for perovskite solar cells (PSCs). Through an iterative design loop, over 100 000 candidates are generated and screened, and randomly selected molecules
Adroit T. N. Fajar +7 more
wiley +1 more source
Reshaping the resilient educational ecosystem in the intelligent era: a case study of the CLIL course of international trade practice. [PDF]
Yin X, Chen F.
europepmc +1 more source
Plantilla de planificació d'unitats didàctiques per AICLE i contextes rics en contingut [PDF]
CLILSI +2 more
core
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv +11 more
wiley +1 more source
How generative AI enhances self-regulated learning in EFL learners: a chain mediation model of "intention to use" and "learning engagement". [PDF]
Xu J.
europepmc +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source

