Results 181 to 190 of about 41,655,511 (287)

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia   +2 more
wiley   +1 more source

In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs

open access: yesAdvanced Intelligent Discovery, EarlyView.
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley   +1 more source

Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction

open access: yesAdvanced Intelligent Discovery, EarlyView.
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

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

open access: yesAdvanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang   +9 more
wiley   +1 more source

Home - About - Disclaimer - Privacy