Results 131 to 140 of about 212,881 (293)

SADASNet: A Selective and Adaptive Deep Architecture Search Network with Hyperparameter Optimization for Robust Skin Cancer Classification

Diagnostics
Background/Objectives: Skin cancer is a major public health concern, where early diagnosis and effective treatment are essential for prevention. To enhance diagnostic accuracy, researchers have increasingly utilized computer vision systems, with deep ...
Günay İlker, İnik Özkan
doaj   +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

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

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

A Data-Driven Prediction Method for Proton Exchange Membrane Fuel Cell Degradation

Energies
This paper proposes a long short-term memory (LSTM) network to predict the power degradation of proton exchange membrane fuel cells (PEMFCs), and in order to promote the performance of the LSTM network, the ant colony algorithm (ACO) is introduced to ...
Dan Wang, Haitao Min, Honghui Zhao, Weiyi Sun, Bin Zeng, Qun Ma   +5 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

Performance Curve Prediction Method for Centrifugal Compressor Based on BOA-BPNN

Shiyou jixie
To enhance the status monitoring accuracy and operation and maintenance intelligence level of compressors， taking PCL803 centrifugal compressor in a natural gas pipeline as an example， a centrifugal compressor performance curve prediction method based on
Zhu Wangyou, Liu Jiahao, Yang Junming, Liu Zhen, Hou Lei   +4 more
doaj  

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

Grid search hyperparameter tuning in additive manufacturing processes

Manufacturing Letters, 2023
Michael Ogunsanya, Joan Isichei, Salil S. Desai   +2 more
semanticscholar   +1 more source