Results 171 to 180 of about 1,378,752 (293)

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
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, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Multicenter Validation of Machine Learning Models for Predicting Myopia Progression Across School‐Based Screening and Optical Intervention Settings in Chinese Children and Adolescents

Advanced Intelligent Discovery, EarlyView.
Machine‐learning models predict myopia trajectories from 12 routine ocular variables in 40 445 children across 10 hospitals. Externally validated across school‐based screening and optical‐intervention settings, the best models achieve AUROC 0.97 for myopia status and R2 0.83 for spherical equivalent, enabling personalized risk stratification to curb ...
Yitong Zhang, Mingxuan Liu, Yifei Chen, Ying Wu, Lijun Zhang, Mengyao Guo, Yulan Yan, Runmei Wei, Zihan Cui, Peng Luo, Fang Chen, Bo Yang, Youcang Han, Xiaoyang Liu, Qiyuan Tian   +14 more
wiley   +1 more source

OXidative Stress PREDictor: A Supervised Learning Approach for Annotating Cellular Oxidative Stress States in Inflammatory Cells

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
OxSpred, an eXtreme‐Gradient‐Boosting‐‐based supervised learning model, accurately annotates oxidative stress in innate immune cells at the single‐cell level, providing interpretable embeddings with significant biological relevance. This innovative tool revolutionizes the understanding of innate immune cell functions during inflammation and enhances ...
Po‐Yuan Chen, Tai‐Ming Ko
wiley   +1 more source

A Survey on Binary Tree Codings [PDF]

The Computer Journal, 1991
openaire   +3 more sources

Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu, Yaxin Liu, Ruiqing Han, Kai Zheng, Yufeng Yao, Ming Zhong   +5 more
wiley   +1 more source

Comparative Analysis of Model‐Agnostic Explanation Methods in Materials Science

Advanced Intelligent Systems, EarlyView.
To address the critical lack of explainable artificial intelligence (XAI) benchmarks in materials science, we present a quantitative and qualitative analysis of six XAI methods applied to molecular fingerprints. Our results reveal significant discrepancies in feature importance rankings, demonstrating that the chosen explanation approach introduces ...
Anna Przybyłowska, Joanna Neubauer, Monika Sztuder, Witold Taisner, Agnieszka Hryniewicka, Julia Kolodziejczyk, Marta Eliza Plonska‐Brzezinska, Dariusz Brzezinski   +7 more
wiley   +1 more source

A Scalable and Resource‐Efficient Pipelined p‐Computer for Probabilistic Ising Machines

Advanced Intelligent Systems, EarlyView.
(a) Block diagram of the portfolio optimization problem: given M assets, the goal is to determine the optimal weights w that maximize the expected return (based on the mean historical assets return u), while minimizing the risk, quantified by the assets covariance matrix S.
Deborah Volpe, Eleonora Raimondo, Andrea Grimaldi, Pedram Khalili Amiri, Stefano Chiappini, Anna Giordano, Mario Carpentieri, Hyunsoo Yang, Massimo Chiappini, Giovanni Finocchio   +9 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

An Integrated Fabric‐Pneumatic Soft Sensing System for Multi‐Site Muscle Activity Decoding

Advanced Intelligent Systems, EarlyView.
Fabric‐pneumatic chambers convert muscle deformation into pressure signals without electronics at the body‐contact sensing interface. A unified processing pipeline enables static posture classification, continuous elbow‐angle estimation, forearm gesture recognition, and knee‐movement detection across three anatomical sites.
Qifeng Xun, Jonathan William Ambrose, Quan Xiong, Chen Hua Yeow   +3 more
wiley   +1 more source

Deep Learning Classification of Pancreatic Cancer Cells Over a Progression of Epithelial to Mesenchymal States by Deformability Cytometry Under Microfluidic Viscoelastic Flows

Advanced Intelligent Systems, EarlyView.
Cancer cells progressively spread over intermediate epithelial‐to‐mesenchymal transition states that cause nuclear enlargement and circular redistribution of filamentous vimentin are classified by deformability cytometry coupled to a multi‐region deep learning model with convolutional feature extraction and attention‐based regional aggregation.
Javad Jarmoshti, Hanyuan Gao, Negin Zeinali, Abdullah‐Bin Siddique, Sara J. Adair, Todd W. Bauer, Matthew J. Lazzara, Xiaoxuan Yang, Nathan S. Swami   +8 more
wiley   +1 more source