Results 91 to 100 of about 2,067 (261)
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
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
Vibration Analysis of Membranes with Arbitrary Sapes Using Discrete Singular Convolution
In this paper, free vibration analysis of curvilinear or straight-sided quadrilateral membranes is presented. In the proposed approach, irregular physical domain is transformed into a rectangular domain by using geometric coordinate transformation. For demonstration of the accuracy and convergence of the method, some numerical examples are provided on ...
openaire +1 more source
Nuevas técnicas de deconvolución dispersa robusta [PDF]
La deconvolución dispersa consiste en estimar una señal de reducido número de muestras no nulas a partir de un conjunto de observaciones ruidosas, que se suponen originadas por la convolución entre una señal de aspecto impulsivo y la respuesta al ...
Martínez Cruz, Carlos Eugenio
core
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +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
A fast convolution method for the fractional Laplacian in $\mathbb{R}$
In this article, we develop a new method to approximate numerically the fractional Laplacian of functions defined on $\mathbb R$, as well as some more general singular integrals.
de la Hoz, Francisco +3 more
core
A zero‐watermarking algorithm that combines a refined convolutional additive self‐attention vision transformer (CAS‐ViT) with a discrete wavelet transform variance‐based feature descriptor (DVFD) is proposed for protecting the privacy of medical images in mobile healthcare services.
Pei Liu +6 more
wiley +1 more source

