Results 91 to 100 of about 93,556 (252)

Potent and Long‐Lasting Immunogenicity Generated by LNP‐mRNA gE Antigen Against Varicella Zoster Virus via an AI‐Assisted Pipeline

Advanced Science, EarlyView.
This study designs a novel mRNA‐LNP vaccine targeting VZV glycoprotein E (gE) for herpes zoster via an AI‐assisted pipeline. Validated in mice and rhesus macaques, the mRNA‐LNP vaccine shows strong humoral and cellular immune responses, with CD4+ T‐cell responses more effective and durable than Shingrix, offering a promising prophylactic option ...
Kai Dong, Fang Liu, Dawei Wang, Yanfen Li, Man Zhang, Yuting Zhou, Gengshen Song   +6 more
wiley   +1 more source

Diffusion‐MRI‐Based Estimation of Cortical Architecture via Machine Learning (DECAM) in Primate Brains

Advanced Science, EarlyView.
We present Diffusion‐MRI‐based Estimation of Cortical Architecture via Machine Learning (DECAM), a deep‐learning framework for estimating primate brain cortical architecture optimized with best response constraint and cortical label vectors. Trained using macaque brain high‐resolution multi‐shell dMRI and histology data, DECAM generates high‐fidelity ...
Tianjia Zhu, Minhui Ouyang, Shufang Tan, Jianlin Guo, Ziqin Zhang, Xuan Liu, Risheng Liu, Hao Huang   +7 more
wiley   +1 more source

Earth System Model Tuning Without Hyperparameters

Journal of Advances in Modeling Earth Systems
Abstract This article introduces a new algorithm, KalmRidge , and demonstrates its ability to tune an Earth system model using idealized experiments. Unlike similar algorithms, KalmRidge eliminates the need for offline hyperparameter selection, thereby substantially reducing
Nikki Lydeen, Timothy DelSole, Benjamin Cash   +2 more
openaire   +2 more sources

CLinNET: An Interpretable and Uncertainty‐Aware Deep Learning Framework for Multi‐Modal Clinical Genomics

Advanced Science, EarlyView.
Identifying disease‐causing genes in neurocognitive disorders remains challenging due to variants of uncertain significance. CLinNET employs dual‐branch neural networks integrating Reactome pathways and Gene Ontology terms to provide pathway‐level interpretability of genomic alterations.
Ivan Bakhshayeshi, Mohammad Mahdi Hosseini, Ahmadreza Argha, Roxana Zahedi, Nigel H. Lovell, Hamid Alinejad‐Rokny   +5 more
wiley   +1 more source

Comment on “De Novo Reconstruction of 3D Human Facial Images from DNA Sequence”

Advanced Science, EarlyView.
This comment examines AI‐driven DNA‐based facial reconstruction, focusing on the Difface model. While such technologies promise biomedical and forensic applications, they pose significant ethical, legal, and methodological challenges. We emphasize transparency, benchmarking, and rigorous validation to avoid misinterpretation and misuse.
Jennifer K. Wagner, Nina Claessens, Caitlin M. Maloney, Peter Claes   +3 more
wiley   +1 more source

Congruent Learning for Self-Regulated Federated Learning in 6G

IEEE Transactions on Machine Learning in Communications and Networking
Future 6G networks are expected to be AI-native with distributed machine learning functionalities responsible for improving and automating a variety of network- and service-management tasks. To enable a privacy-preserving approach to distributed learning,
Jalil Taghia, Farnaz Moradi, Hannes Larsson, Xiaoyu Lan, Adam Orucu, Masoumeh Ebrahimi, Andreas Johnsson   +6 more
doaj   +1 more source

MGM as a Large‐Scale Pretrained Foundation Model for Microbiome Analyses in Diverse Contexts

Advanced Science, EarlyView.
We present the Microbial General Model (MGM), a transformer‐based foundation model pretrained on over 260,000 microbiome samples. MGM learns contextualized microbial representations via self‐supervised language modeling, enabling robust transfer learning, cross‐regional generalization, keystone taxa discovery, and prompt‐guided generation of realistic,
Haohong Zhang, Yuli Zhang, Zixin Kang, Jiayun Xiong, Ronghua Yang, Kang Ning   +5 more
wiley   +1 more source

The Implementation of Bayesian Optimization for Automatic Parameter Selection in Convolutional Neural Network for Lung Nodule Classification

Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
Lung cancer's high mortality rate makes early detection crucial. Machine learning techniques, especially convolutional neural networks (CNN), play a very important role in lung nodule detection.
Kadek Eka Sapta Wijaya, Gede Angga Pradipta, Dadang Hermawan   +2 more
doaj   +1 more source

HiST: Histological Images Reconstruct Tumor Spatial Transcriptomics via MultiScale Fusion Deep Learning

Advanced Science, EarlyView.
HiST, a multiscale deep learning framework, reconstructs spatially resolved gene expression profiles directly from histological images. It accurately identifies tumor regions, captures intratumoral heterogeneity, and predicts patient prognosis and immunotherapy response.
Wei Li, Dong Zhang, Eryu Peng, Shijun Shen, Hamid Alinejad‐Rokny, Yao Liu, Junke Zheng, Cizhong Jiang, Youqiong Ye   +8 more
wiley   +1 more source

Cardiovascular disease detection from cardiac arrhythmia ECG signals using artificial intelligence models with hyperparameters tuning methodologies

Heliyon
Cardiovascular disease (CVD) is connected with irregular cardiac electrical activity, which can be seen in ECG alterations. Due to its convenience and non-invasive aspect, the ECG is routinely exploited to identify different arrhythmias and automatic ECG
Gowri Shankar Manivannan, Harikumar Rajaguru, Rajanna S, Satish V. Talawar   +3 more
doaj   +1 more source