Results 151 to 160 of about 22,751 (263)

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, Volume 2, Issue 5, October 2026.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

A Multimodal Deep Learning Based Framework for Early and Accurate Diagnosis of Depression Using Electroencephalography and Event‐Related Potential Signals

Applied AI Letters, Volume 7, Issue 3, October 2026.
Cross Wavelet Transform (XWT) is combined with a pre‐trained AlexNet to extract rich time‐frequency features from non‐stationary EEG signals. Also, the proposed framework simultaneously extracts and integrates spatial (Node2vec), time‐frequency (XWT + AlexNet), and spectral (PSD + TSCN) features from EEG and ERP signals within a parallel architecture ...
Atefeh Abedzadeh Attar, Mohammad Hossein Moattar, Yahya Forghani   +2 more
wiley   +1 more source

Structurally Cascaded Physics‐Informed Graph Neural Networks for Mechanotransduction‐Aware Tumor Microenvironment Modeling

Applied Research, Volume 5, Issue 5, October 2026.
This study introduces a structurally cascaded physics‐informed graph neural network to model tumor microenvironments accurately. By enforcing a directional dependency from mechanical strain to biochemical secretion, the method eliminates unphysical artifacts and significantly improves predictive accuracy for precision healthcare applications.
Xinyuan Chen, Nurashikin Saaludin, Mohd Nizam Husen   +2 more
wiley   +1 more source

Artificial Intelligence in Gastric Cancer: Diagnostic, Prognostic, and Predictive Developments, Evidence Maturity, and Translational Challenges

Cancer Reports, Volume 9, Issue 10, October 2026.
ABSTRACT Background Gastric cancer (GC) remains a major global health burden characterized by substantial heterogeneity in diagnosis, prognosis, and treatment response. Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), has been increasingly investigated for the analysis of endoscopic images, radiological scans, whole‐
Chong Chen, Weisong Xu, Tong Wu, Junpeng Zhao, Xuebing Xu, Mingbing Xiao, Kang Xu   +6 more
wiley   +1 more source

Pattern‐Based P53 Immunohistochemistry Predicts Recurrence in Colorectal Liver Metastases Without Complete Pathologic Response After Neoadjuvant Chemotherapy

Cancer Reports, Volume 9, Issue 10, October 2026.
ABSTRACT Background Aberrant p53 expression may have prognostic significance in colorectal cancer; however, its role in patients with colorectal liver metastases (CRLM) who receive neoadjuvant chemotherapy but do not achieve pathological complete response (pCR) remains unclear.
Phat Thi Hong Ho, Duy Duc Nguyen, Vuong Dinh Thy Hao, Giang Huong Tran, Lam Viet Trung, Thinh Van Hoang, Hoang Bac Nguyen   +6 more
wiley   +1 more source

Quantifying Shuttlecock Skill Progression via Multimodal Action Recognition and Dynamics‐Guided Trajectory Prediction

Engineering Reports, Volume 8, Issue 10, October 2026.
This study proposes a multimodal feature fusion‐based action recognition and trajectory prediction framework to quantitatively evaluate the effectiveness of compensatory exercises in accelerating shuttlecock skill acquisition. The system comprehensively employs TrackNet, Faster R‐CNN, and HRNet to extract shuttlecock trajectories, player positions, and
Chao Zhang, Fei Zeng
wiley   +1 more source

Synergistic N‑Vacancy and S‑Scheme Engineered CaF₂/g‑C₃N₄ Heterojunction for Photocatalytic Aromatic Phenol Degradation: DFT, Phytotoxicity, and Environmental Impact. [PDF]

ACS Omega
Dhar D, Sengupta S.
europepmc   +1 more source

Adversarially Regularized Dynamic Graph Embeddings for Robust Community Evolution and Threat Detection in OSN

Engineering Reports, Volume 8, Issue 10, October 2026.
An adversarially regularized, carbon‐aware dynamic graph framework enables robust threat detection in evolving social networks by integrating temporal embeddings, community tracking, and sequential threat profiling. The approach achieves ∼95%–96% accuracy while reducing training energy consumption by 40%–45%, supporting scalable real‐world deployment ...
Romil Rawat, Ashish Dibouliya, Antonio González‐Torres, Ranjana Sikarwar, A. Samson Arun Raj, Yagyanath Rimal   +5 more
wiley   +1 more source

Identification of YES1 Inhibitors From Approved Drugs Using a Multimodal Deep Learning Framework

Molecular Informatics, Volume 45, Issue 10, October 2026.
To overcome anti‐HER2 drug resistance, we developed a multimodal deep learning model to identify YES1 inhibitors from approved drugs. By integrating molecular graphs, physicochemical properties, and protein sequence data, our computational screening identified chlorpromazine and raloxifene.
Takayoshi Kawabata, Tatsuaki Takeda, Yuta Tanaka, Soichiro Ushio, Akira Miyamoto, Koki Nakagomi, Tomonori Sakai, Risa Maruyama, Takashi Makita, Hirofumi Hamano, Shinichi Toyooka, Yoshito Zamami   +11 more
wiley   +1 more source

PH-GCN: Boosting Human Action Recognition Through Multi-Level Granularity With Pair-Wise Hyper GCN

Recently, there has been a surge of interest in utilizing Graph Convolutional Networks (GCNs) for skeleton- based action recognition, where learning effective representations of the skeletal graph is of paramount importance for attaining success in this ...
Tamam Alsarhan, Iyyakutti Iyappan Ganapathi, Naoufel Werghi, Syed Sadaf Ali, Ahmad Ali   +4 more
core   +1 more source