Results 111 to 120 of about 118,657 (309)

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

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

Advanced 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

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

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
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

Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining

Advanced Intelligent Systems, EarlyView.
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson, Nebojša Maleševic, Anders Björkman, Christian Antfolk   +3 more
wiley   +1 more source

Design and Integration of an Elastic Sensor Sheet for Pressure Ulcer Prediction: Materials, Methods, and Network Connections

Proceedings
This paper discusses the design and integration of an elastic sensor sheet for SENSOMATT, a smart device that predicts pressure ulcers caused by prolonged skin pressure.
Mohammad Mohammad Amini, Davood Fanaei Sheikholeslami, Rogério Dionísio, Ahmadreza Heravi, Mahdi Faghihi   +4 more
doaj   +1 more source

Determining the Minimal Clinically Important Difference of the 40‐Item Smell Identification Test in People With Cystic Fibrosis

International Forum of Allergy &Rhinology, EarlyView.
ABSTRACT Background Chronic rhinosinusitis (CRS) and olfactory dysfunction (OD) are highly prevalent among people with cystic fibrosis (PwCF) and negatively impact quality of life. The 40‐item Smell Identification Test (SIT) is widely used to assess psychophysical olfaction, but a CF‐specific minimal clinically important difference (MCID) has not been ...
Eugene Oh, Jessa E. Miller, Michelle J. Lee, Anna Zemke, David Baraghoshi, Matthew J. Strand, Jeremiah A. Alt, Todd E. Bodner, Michael Chang, Naweed I. Chowdhury, Patricia H. Eshaghian, Anne E. Getz, Jennifer L. Goralski, David A. Gudis, Peter H. Hwang, Ashoke Khanwalkar, Adam J. Kimple, Jivianne T. Lee, Douglas A. Li, Jess C. Mace, Jayakar V. Nayak, Jonathan B. Overdevest, Zara Patel, Daniella K. Safatian, Rodney J. Schlosser, Brent Senior, Amanda L. Stapleton, Timothy L. Smith, Zachary M. Soler, Jeffrey D. Suh, Grant A. Turner, Marilene B. Wang, Milene T. Saavedra, Jennifer L. Taylor‐Cousar, Daniel M. Beswick   +34 more
wiley   +1 more source

LDA model

LDA model used for the domain application ...
openaire   +1 more source

Spectroscopic and In Silico Determination of the Structural and Antioxidant Properties of Essential Oils From Lavandula Species Cultivated in the Silivri Region of Istanbul

Journal of the American Oil Chemists' Society, EarlyView.
ABSTRACT Plants are important sources of bioactive compounds that contribute to nutrition, health maintenance, and disease prevention. In this study, the chemical composition and antioxidant potential of essential oils obtained from Lavandula angustifolia “Sevtopolis” and Lavandula × intermedia cultivated in the Silivri region of Istanbul were ...
Bilge Bicak, Beray Kizilkaya, Serda Kecel Gunduz, Aliye Demet Demirag, Sabriye Percin Ozkorucuklu   +4 more
wiley   +1 more source

Comprehensive DFT Analysis of FeSi and RhSi: Structural Stability, Electronic Contrast and Transport‐Optical Responses

Advanced Physics Research, EarlyView.
This comprehensive density functional theory analysis investigates the structural, electronic, optical, mechanical, and thermoelectric properties of FeSi, c‐RhSi, and o‐RhSi. Results reveal distinct electronic and optical contrasts among the materials.
Md Farhan Hassan, Shaher Azad, Md Salim Hossain, Suptajoy Barua, Md Kamruzzaman   +4 more
wiley   +1 more source