Results 131 to 140 of about 120,623 (302)
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
Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry
Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa +3 more
wiley +1 more source
Is there a relation between trust and trustworthiness? [PDF]
We provide new evidence about a positive correlation between the own amount sent and the own amount returned in the investment game. Our analysis relies on experimental data collected under the strategy method for establishing our main result.
Tamás Kovács, Marc Willinger
core
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed +15 more
wiley +1 more source
Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong +4 more
wiley +1 more source
I argue that trustworthiness is an epistemic desideratum. It does not reduce to justified or reliable true belief, but figures in the reason why justified or reliable true beliefs are often valuable. Such beliefs can be precarious.
Elgin, CZ
core +1 more source
Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source
On Trustworthiness Recommendation.
Heutzutage werden das Internet und Online-Soziale-Netze als bevorzugtes Medium für Kommunikation, Geschäftsbeziehungen und finanzielle Transaktionen verwendet. Der technologische Fortschritt erweitert insbesondere die Möglichkeiten zur Interaktion über große Distanzen. Ein gewisses Risiko stellen jedoch Erstkontakte dar.
openaire +2 more sources
Lavish Returns on Cheap Talk: Non-binding Communication in a Trust Experiment [PDF]
We let subjects interact with anonymous partners in trust (investment) games with and without one of two kinds of pre-play communication: numerical (tabular) only, and verbal and numerical.
Avner Ben-Ner, Ting Ren, Louis Putterman
core
An agentic AI‐driven decision‐support framework for prosumers is proposed, integrating PV generation, load profiling, and multihorizon optimization within a four‐agent architecture. The approach significantly reduces grid dependence, enhances self‐sufficiency and prevents system oversizing.
Adela BÂRA, Simona‐Vasilica OPREA
wiley +1 more source

