Results 151 to 160 of about 156,806 (296)

PEAO: a bio-inspired parallel optimizer with a multi-strategy communication mechanism for breast cancer diagnosis. [PDF]

Sci Rep
Li H, Govindarajan V, Ang TF, Ayadi M, Ku CS, Leong MC, Shabaruddin FH, Ishak WZW, Por LY.   +8 more
europepmc   +1 more source

Parsing Reward Processing Substages With Multimodal EEG–fMRI

Human Brain Mapping, Volume 47, Issue 3, February 15, 2026.
Reward processing is complex and parsing anticipatory from consummatory substages will develop a more specific taxonomy of neural motivation and pleasure systems. Our multimodal data indicate EEG–fMRI covariance linking reward feedback EEG measures to dACC‐striatal regions, while reward anticipation EEG measures covaried with motor planning and ...
Ken J. Lau, Brian J. Roach, Samantha Abram, Spero C. Nicholas, Clay B. Holroyd, Elhum A. Shamshiri, Martin Paulus, Judith M. Ford, Daniel H. Mathalon, Susanna L. Fryer   +9 more
wiley   +1 more source

Enhancing the LEACH protocol and lightweight chaotic cryptography for secure data transmission in wireless sensor networks. [PDF]

Sci Rep
Zarei M, Fatehi Dindarlou MH, Taghizadeh M, Jamali J.   +3 more
europepmc   +1 more source

Materials and System Design for Self‐Decision Bioelectronic Systems

Advanced Materials, Volume 38, Issue 9, 12 February 2026.
This review highlights how self‐decision bioelectronic systems integrate sensing, computation, and therapy into autonomous, closed‐loop platforms that continuously monitor and treat diseases, marking a major step toward intelligent, self‐regulating healthcare technologies.
Qiankun Zeng, Hong Liu, Yongheng Zhang, Youbin Zheng, Xuyin Ding, Mengni Zhu, Guoyue Shi, Yan Wang, Hossam Haick, Min Zhang   +9 more
wiley   +1 more source

Optimizing solar power forecasting with metaheuristic algorithms and deep learning models for photovoltaic grid connected systems. [PDF]

Sci Rep
Mohamad Radzi PNL, Mekhilef S, Mohamed Shah N, Akhter MN, Seyedmahmoudian M, Stojcevski A.   +5 more
europepmc   +1 more source

Inferring Gene Regulatory Networks From Single‐Cell RNA Sequencing Data by Dual‐Role Graph Contrastive Learning

Advanced Science, Volume 13, Issue 9, 13 February 2026.
RegGAIN is a novel and powerful deep learning framework for inferring gene regulatory networks (GRNs) from single‐cell RNA sequencing data. By integrating self‐supervised contrastive learning with dual‐role gene representations, it consistently outperforms existing methods in both accuracy and robustness.
Qiyuan Guan, Jiating Yu, Jieyi Pan, Fan Yuan, Jiadong Ji, Rusong Zhao, Zhi‐Ping Liu, Bingqiang Liu, Ling‐Yun Wu, Duanchen Sun   +9 more
wiley   +1 more source

WHFDL: an explainable method based on World Hyper-heuristic and Fuzzy Deep Learning approaches for gastric cancer detection using metabolomics data. [PDF]

BioData Min
Mahdavi N, Daliri A, Zabihimayvan M, Yaghooti Y, Mir MM, Ghazanfari P, Zarrabi A, Khalaj P, Sadeghi R.   +8 more
europepmc   +1 more source

SKALE: An Interpretable Multiscale Machine Learning Model for Decoding Phase‐Specific Protein Aggregation in Neurodegenerative Proteinopathies

Aggregate, Volume 7, Issue 2, February 2026.
Protein aggregation drives diverse degenerative diseases, yet its molecular origins are difficult to predict. SKALE uses interpretable machine learning to link sequence, structure, and dynamics, revealing how local structural weakening triggers aggregation.
Wei Xuan Wilson Loo, Jia Shen Sio, Keyin Yap, Yan Shan Loo, Hui Xuan Lim, Shuangyue Zhang, Huitao Liu, Chen Seng Ng   +7 more
wiley   +1 more source

Corrigendum to "Improving photovoltaic cell parameter calculations through a puffer fish inspired optimization technique" [Heliyon Volume 10, Issue 13, July 2024, Article e33952]. [PDF]

Heliyon
Singla MK, Gupta J, Parag N, Ekta T, Tella TG, Mosaad MI, Murodbek S.   +6 more
europepmc   +1 more source

Predicting Audit Reports Using Meta-Heuristic Algorithms

Journal of Distribution Science, 2013
Hashem Valipour, Fatemeh Salehi, Mostafa Bahrami   +2 more
openaire   +1 more source