Results 131 to 140 of about 109,092 (251)

A Comparative Analysis of Different Machine Learning Algorithms Developed with Hyperparameter Optimization in the Prediction of Student Academic Success

Applied Sciences
Machine learning makes significant contributions in many areas of the applied sciences. One of these is the field of education, in the form of predicting students’ academic success and developing educational policies.
Bahar Demirtürk, Tuba Harunoğlu
doaj   +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

Pathomics Signature for Prognosis and CA19‐9 Interception in Pancreatic Ductal Adenocarcinoma: A Real‐Life, Multi‐Center Study

Advanced Science, EarlyView.
This study develops a deep learning‐based pathomics model to predict survival outcomes in pancreatic cancer patients. The CrossFormer architecture analyzes routine H&E‐stained tissue slides, identifying key prognostic features including stromal patterns, cellular characteristics, and immune infiltration.
Qiangda Chen, Zhihang Xu, Yiping Zou, Zhenlai Jiang, Yecheng Li, Taochen He, Hanlin Yin, Jiali Li, Yanfei An, Jiande Han, Yuqi Xie, Wei Gan, Yaolin Xu, Wenquan Wang, Junyi He, Haibo Wang, Wenchuan Wu, Zhenyu Ye, Wenhui Lou, Jihui Hao, Liang Liu, Jun Yu, Ning Pu   +22 more
wiley   +1 more source

Comparison of Particle Swarm Optimization Algorithms in Hyperparameter Optimization Problem of Multi Layered Perceptron

Computer Assisted Methods in Engineering and Science
This paper describes the application of particle swarm optimization (PSO) for the hyperparameter optimization problem of multi-layered perceptron (MLP) model.
Kenta Shiomi, Tetsuya Sato, Eisuke Kita
doaj   +1 more source

S3RL: Enhancing Spatial Single‐Cell Transcriptomics With Separable Representation Learning

Advanced Science, EarlyView.
Separable Spatial Representation Learning (S3RL) is introduced to enhance the reconstruction of spatial transcriptomic landscapes by disentangling spatial structure and gene expression semantics. By integrating multimodal inputs with graph‐based representation learning and hyperspherical prototype modeling, S3RL enables high‐fidelity spatial domain ...
Laiyi Fu, Penglei Wang, Gaoyuan Xu, Jitao Lu, Qinke Peng, Danyang Wu, Hequan Sun   +6 more
wiley   +1 more source

Accurate Identification of Protein Binding Sites for All Drug Modalities Using ALLSites

Advanced Science, EarlyView.
ALLSites is a unified sequence‐based framework for identifying proteome‐wide binding sites across all drug modalities. It integrates a gated convolutional network with a transformer architecture to capture residue interactions directly from the sequence.
Minjie Mou, Mingkun Lu, Zhimeng Zhou, Yanlin Ren, Xinyuan Yu, Ziqi Pan, Yuan Zhou, Hao Yang, Lingyan Zheng, Shukai Gu, Yang Zhang, Wei Hu, Fengcheng Li, Haibin Dai, Feng Zhu   +14 more
wiley   +1 more source

From Natural Discovery to AI‐Guided Design: A Curated Collection of Compact Enhancers for Crop Engineering

Advanced Science, EarlyView.
ABSTRACT Precise transgene‐free gene upregulation remains a challenge in crop biotechnology, as conventional enhancers often exceed CRISPR‐mediated knock‐in size constraints and face regulatory hurdles. Here we establish a foundational cross‐species resource of compact transcriptional enhancers developed via STEM‐seq, a high‐throughput screening ...
Qi Yao, Jin Gao, Keling Wang, Yufeng Liu, Peijin Han, Hong Pan, Xiaofeng Yang, Qianlan Yin, Dating Zhong, Lu Ye, Qi Deng, Lingling Gao, Xiaoyu Tu, Dequan Wang, Yuming Lu   +14 more
wiley   +1 more source

Hyperparameter optimization for cardiovascular disease data-driven prognostic system. [PDF]

Vis Comput Ind Biomed Art, 2023
Saputra J, Lawrencya C, Saini JM, Suharjito S.   +3 more
europepmc   +1 more source