Results 191 to 200 of about 52,212 (299)

BrainInsights: a comprehensive framework for pre-processing, analysis, and interpretation of neuroimaging data using traditional statistics and machine learning. [PDF]

Front Neuroinform
Selvakumar M, Mendez Torrijos A, Konerth LC, Horndasch S, Atreya R, Doerfler A, Schett G, Rech J, Hess A.   +8 more
europepmc   +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

Automated Processing and Deviation Analysis of 3D Pipeline Point Clouds Based on Geometric Features. [PDF]

J Imaging
Jin S, Fu K, Yang C, Rui H.
europepmc   +1 more source

Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry

Advanced Intelligent Discovery, EarlyView.
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, Erving Ximendes, Luís D. Carlos, Carlos D. S. Brites   +3 more
wiley   +1 more source

Advances in Electrofusion Welding Technology for Polymeric Pipelines: From Process Optimization to Mechanism-Driven Control. [PDF]

Polymers (Basel)
Hong B, Sun Z, Wu Z, Meng Y, Chen Z, Chen X, Wang W, Liu D.   +7 more
europepmc   +1 more source

Pipeline Inspection using Microwave Nondestructive Testing

A Master of Science thesis in Electrical Engineering by Ahmad Ghattas entitled, “Pipeline Inspection using Microwave Nondestructive Testing”, submitted in January 2025. Thesis advisor is Dr. Nasser Qaddoumi and thesis co-advisor is Dr. Amer Zakaria. Soft
Ghattas, Ahmad
core  

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

A Reproducible COCO-Polygon Quality-Control Pipeline Improves Segmentation Stability in Endoscopic Airway Imaging. [PDF]

Diagnostics (Basel)
Atmaca M, Kervancı IS, Olgun N.
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

A Dataset of Microelectrode Recordings from Deep Brain Stimulation Procedures. [PDF]

Sci Data
Osowska K, Szymański J, Libionka W.
europepmc   +1 more source