Results 191 to 200 of about 379,690 (315)
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
The dynamics of cooperation in asymmetric public goods games. [PDF]
Wang X, Hilbe C, Zhang B.
europepmc +1 more source
Cooperating to Resist Coercion: An Experimental Study [PDF]
This study sheds light on the difficulties people face in cooperating to resist coercion. We adapt a threshold public goods game to investigate whether people are able to cooperate to resist coercion despite individual incentives to free-ride.
Ann B. Gillette +2 more
core
Large Language Model‐Based Chatbots in Higher Education
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
Effect of emotional migration on Cooperation for public goods games on continuous two-dimensional space. [PDF]
Ji Y, Tan M, Long H.
europepmc +1 more source
ENDOGENOUS MOVE STRUCTURE AND VOLUNTARY PROVISION OF PUBLIC GOODS: THEORY AND EXPERIMENT [PDF]
In this paper we examine voluntary contributions to a public good, embedding Varian (1994)’s voluntary contribution game in extended games that allow players to choose the timing of their contributions.
Daniele Nosenzo, Martin Sefton
core
Reciprocity and Overoptimism in Public Goods Games
Wolfgang Breuer, Anselm Hüwe
openalex +1 more source
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley +1 more source

