Results 131 to 140 of about 127,719 (261)

Assessing the Relative Importance of Imaging and Serum Biomarkers in Capturing Disability, Cognitive Impairment, and Clinical Progression in Multiple Sclerosis

Advanced Science, EarlyView.
Using machine‐learning analyses in two independent multiple sclerosis cohorts, spinal cord atrophy and cortical degeneration emerged as key predictors of disability and progression independent of relapses. Deep gray matter damage further improved prediction, while serum biomarkers of brain damage provided complementary information, highlighting the ...
Alessandro Cagol, Pascal Benkert, Sabine Schaedelin, Mario Ocampo‐Pineda, Noemi Montobbio, Po‐Jui Lu, Batuhan Ayci, Antonia Wenger, Alfi Aran Shukur, Kornelius Kaim, Lester Melie‐Garcia, Matthias Weigel, Alessio Signori, Pasquale Calabrese, Ludwig Kappos, Maria Pia Sormani, Jens Kuhle, Cristina Granziera   +17 more
wiley   +1 more source

AOA-guided hyperparameter refinement for precise medical image segmentation

Alexandria Engineering Journal
Medical image segmentation faces significant challenges, including the need for extensive annotated data, the impact of hyperparameters, and the limitations of traditional CNN models.
Hossam Magdy Balaha, Waleed M. Bahgat, Mansourah Aljohani, Amna Bamaqa, El-Sayed Atlam, Mahmoud Badawy, Mostafa A. Elhosseini   +6 more
doaj   +1 more source

Proteogenomic Characterization Reveals Subtype‐Specific Therapeutic Potential for HER2‐Low Breast Cancer

Advanced Science, EarlyView.
Multiomic profiling of HER2‐low breast cancer identifies three proteomic subtypes with distinct therapeutic strategies: endocrine, antiangiogenic, and anti‐HER2 therapies. Genomic and lactate modification landscapes are detailed, providing insights for precise management.
Shouping Xu, Keda Yu, Lei Liu, Qin Wang, Xiaohui Wu, Yihai Chen, Guozheng Li, Xin Zhang, Bo Wei, Zitong Fu, Abiyasi Nanding, Zuxianglan Zhao, Lingbing Yang, Xingda Zhang, Jianyu Wang, Wantong Sun, Yi Hao, Zhongyi Cheng, Xiaojiang Cui, Hao Wu, Da Pang   +20 more
wiley   +1 more source

DualPG‐DTA: A Large Language Model‐Powered Graph Neural Network Framework for Enhanced Drug‐Target Affinity Prediction and Discovery of Novel CDK9 Inhibitors Exhibiting in Vivo Anti‐Leukemia Activity

Advanced Science, EarlyView.
This study introduces DualPG‐DTA, a framework integrating two pre‐trained models to generate molecular and protein representations. It constructs dual graphs processed by specialized neural networks with dynamic attention for feature fusion, achieving superior benchmark performance.
Yihao Chen, Jindi Huang, Cong Liu, Shipeng Zhang, Xinze Li, Zhang Zhang, Tie‐Gen Chen, Ling Wang   +7 more
wiley   +1 more source

Hyperparameter Optimization in Machine Learning

Foundations and Trends® in Machine Learning
Hyperparameters are configuration variables controlling the behavior of machine learning algorithms. They are ubiquitous in machine learning and artificial intelligence and the choice of their values determines the effectiveness of systems based on these technologies.
Franceschi, Luca, Donini, Michele, Perrone, Valerio, Klein, Aaron, Archambeau, Cédric, Seeger, Matthias, Pontil, Massimiliano, Frasconi, Paolo   +7 more
openaire   +2 more sources

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

HIDF: Integrating Tree‐Structured scRNA‐seq Heterogeneity for Hierarchical Deconvolution of Spatial Transcriptomics

Advanced Science, EarlyView.
The prevailing neglect of cellular hierarchies in current spatial transcriptomics deconvolution often obscures cellular heterogeneity and impedes the identification of fine‐grained subtypes. To address this issue, HIDF employs a cluster‐tree and dual regularization to systematically model cellular hierarchical structures.
Zhiyi Zou, Yuting Bai, Bo Wang, Wanwan Shi, Xiao Liang, Jiawei Luo   +5 more
wiley   +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

A Deep Representation Learning Method for Quantitative Immune Defense Function Evaluation and Its Clinical Applications

Advanced Science, EarlyView.
ImmuDef, a novel algorithm to quantitatively evaluate the anti‐infection immune defense function of an individual based on RNA‐seq data via a variational autoencoder (VAE) model. It is validated on 3200+ samples across four immune states with high accuracy. It can serve as a metric for disease severity and prognosis across pathogenic cohorts.
Zhen‐Lin Tan, Tao Luo, Yu Lin, Xiao‐Jun Wu, Wen‐Kang Shen, Jie Chen, Qian Lei, An‐Yuan Guo   +7 more
wiley   +1 more source

Modified particle swarm optimization (MPSO) optimized CNN’s hyperparameters for classification

IJAIN (International Journal of Advances in Intelligent Informatics)
This paper proposes a convolutional neural network architectural design approach using the modified particle swarm optimization (MPSO) algorithm. Adjusting hyper-parameters and searching for optimal network architecture from convolutional neural networks
Murinto Murinto, Sri Winiarti
doaj   +1 more source