Results 201 to 210 of about 13,735 (297)

HiSTaR: identifying spatial domains with hierarchical spatial transcriptomics variational autoencoder. [PDF]

J Transl Med
Yu J, Yuan J, Yi Q, Ye Z, Xu P, Liu W.
europepmc   +1 more source

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

Daily Residential Natural Gas Demand Forecasting Using Machine Learning Regression: Comparative Evaluation With a Case Study in Qazvin Province, Iran

Energy Science &Engineering, EarlyView.
This graphical abstract summarizes the proposed framework for improving short‐term residential natural gas consumption forecasting by integrating a novel socioeconomic indicator, the subscription growth ratio (SGR), with conventional meteorological variables.
Ali Pirzad, Mostafa Khanzadi
wiley   +1 more source

MLN2SVG: domain-aware spatially variable gene detection using contrastive variational autoencoder and multi-level neighbor search. [PDF]

Brief Bioinform
Hussain S, Ayoub M, Ye F, Liu X.
europepmc   +1 more source

Microbiome and aging: Trajectories of microbiome age across human ecosystems and their systemic effects

iMeta, EarlyView.
Microbiome age (MA) has emerged as an innovative biomarker of biological aging, reflecting host aging trajectories through dynamic alterations in microbial composition, function, and host–microbe interactions across multiple body ecosystems. Diverse computational strategies—including traditional machine learning, deep learning, and multi‐omics ...
Zhexin Ni, Jiaojiao Xie, Zhichun Zhang, Keming Zhang, Jie Ding, Mingyang Chang, Ying Su, Yunan Zhang, Mingfei Yao, Chengyuan Wang, Yan Yan, Wenjie Fang, Hainv Gao, Xuecong Tian, Yangshuo Li, Xinlin Zhu, Wen Zhang, Wanqing Liao, Gaoyuan Xu, Guojing Chen, Xiaoyi Lv, Chaoqin Yu, Weihua Pan, Vadim Molodtsov, Lanjuan Li, Yue Gao, Wei Zhou   +26 more
wiley   +1 more source

Early damage detection in bridges using a variational autoencoder-based hybrid unsupervised learning framework. [PDF]

Sci Rep
Pakzad SS, Masoodi AR.
europepmc   +1 more source

Intelligent design of artificial biocatalyst for biomedical diseases

Journal of Intelligent Medicine, EarlyView.
This review summarizes recent advances in the intelligent design of artificial biocatalysts for biomedical diseases. By leveraging tailored design strategies, including environment‐responsive engineering and rational/artificial intelligence‐aided optimization, these biocatalysts enable precise modulation of pathological microenvironments and targeted ...
Lijie Zhang, Nan Song, Huanhuan Qiao, Si Sun   +3 more
wiley   +1 more source

Unsupervised Variational-Autoencoder-Based Analysis of Morphological Representations in Magnetic-Nanoparticle-Treated Macrophages. [PDF]

Bioengineering (Basel)
Hwang SY, Kang TI, Kim HS, Hong S, Park JO, Kang B.   +5 more
europepmc   +1 more source

Deep learning cone‐beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects

Journal of Periodontology, EarlyView.
Abstract Background The accurate assessment of infraosseous periodontal defects is crucial for effective diagnosis and treatment planning. Cone‐beam computed tomography (CBCT) enables detailed imaging of these defects; however, to leverage their full potential, CBCT images must be reconstructed in 3 dimensions (3D).
Daniel Palkovics, Balint Molnar, Csaba Pinter, David García‐Mato, Andres Diaz‐Pinto, Attila Tanacs, Andrea Dobos, Peter Windisch, Christoph A. Ramseier   +8 more
wiley   +1 more source

Proposed dense variational autoencoder model integrated with contrastive learning for foot ulcer classification. [PDF]

Sci Rep
Shandilya G, Gupta S, Gupta D, Juneja S, Chadaga K, Nauman A, Al-Masri AA.   +6 more
europepmc   +1 more source