Results 201 to 210 of about 3,885,736 (246)

A review of FDG-PET biomarker analysis methods in Parkinson's disease. [PDF]

J Parkinsons Dis
Reimers E, Bevington C, Stoessl AJ, Sossi V.   +3 more
europepmc   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Graph theory-based machine learning for automated fibromyalgia diagnosis using fMRI during an emotional task. [PDF]

PLoS One
Solouki L, Shahsavari S, Sharini H, Hashemian AH, Johann Schmid V, Jafari S, Rouhi S, Mahaki B.   +7 more
europepmc   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

Neurophysiological Characterization of ADHD in Children Using EEG Signals: A Machine Learning Approach to Executive Function Networks. [PDF]

Sensors (Basel)
Gutiérrez-Jácome DB, Campos-Ortuño RA, Pardo-Valenzuela JE, Gómez-Morales ÓW.   +3 more
europepmc   +1 more source

Construction of Sabatier Volcanoes for CO2 Hydrogenation to C1‐2 Oxygenates Using Data‐Efficient Machine Learning

Advanced Science, EarlyView.
A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley   +1 more source

Development of a predictive model for adverse outcomes after unilateral biportal endoscopic spine surgery in the treatment of lumbar disc herniation using six interpretable machine learning models. [PDF]

Front Surg
Tan Y, Xi Y, Hu N, Liu L, Xu L.
europepmc   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Machine learning and multi-omics analyses reveal CLDN1 as a candidate marker associated with colorectal cancer invasion and nutlin-3a (-) response. [PDF]

Transl Oncol
Shan W, Li Q, Yuan W, Feng R, Hu P, Song Z, Li Y, Luo C, Lei N, Zhang H, Wang Z.   +10 more
europepmc   +1 more source