Results 101 to 110 of about 93,556 (252)

Cancer‐Like Fragmentomic Characteristics of Somatic Variants in Cell‐Free DNA

Advanced Science, EarlyView.
We report that in non‐cancerous subjects, cell‐free (cfDNA) molecules harboring somatic variants exhibit cancer‐like fragmentomic characteristics associated with clonal hematopoiesis. Importantly, these somatic variant‐associated fragmentomic aberrations are more pronounced in cancer patients. Leveraging such somatic variant‐associated signals in cfDNA,
Zhenyu Zhang, Yunyun An, Mengqi Yang, Yuqi Pan, Xiaoyi Liu, Fanglei Gong, Huizhen Lin, Bianbian Tang, Yunxia Bai, Xin Zhao, Yu Zhao, Changzheng Du, Kun Sun   +12 more
wiley   +1 more source

Optimizing Machine Learning Models for Graduation on Time Prediction: A Comparative Study with Resampling and Hyperparameter Tuning

JOIN: Jurnal Online Informatika
Timely graduation prediction is a crucial issue in higher education, especially when academic, demographic, and behavioral factors interact in complex ways.
Rizal Bakri, Syamsu Alam, Niken Probondani Astuti, Muhammad Ilham Bakhtiar   +3 more
doaj   +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

Online Hyperparameter Tuning in Bayesian Optimization for Material Parameter Identification: An Application in Strain-Hardening Plasticity for Automotive Structural Steel

AppliedMath
Effective identification of strain-hardening parameters is essential for predictive plasticity models used in automotive applications. However, the performance of Bayesian optimization depends strongly on kernel hyperparameters in the Gaussian-process ...
Teng Long, Leyu Wang, Cing-Dao Kan, James D. Lee   +3 more
doaj   +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

The Use of Hyperparameter Tuning in Model Classification: A Scientific Work Area Identification

JOIV: International Journal on Informatics Visualization
This research aims to investigate the effectiveness of hyperparameter tuning, particularly using Optuna, in enhancing the classification performance of machine learning models on scientific work reviews. The study focuses on automating the classification
Nadya Alinda Rahmi, Sarjon Defit, - Okfalisa   +2 more
doaj   +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

Deep Learning‐Powered Scalable Cancer Organ Chip for Cancer Precision Medicine

Advanced Science, EarlyView.
This scalable, low‐cost Organ Chip platform, made via injection molding, uses capillary pinning for hydrogel confinement and supports versatile tissue coculture and robust imaging. Deep learning enables label‐free, sensitive phenotypic analysis.
Yu‐Chieh Yuan, Beibei Xu, Jenna McCormack, XuHai Huang, Jingzhe Ma, Thomas Marshall, Yacong Sun, Hardeep Singh, Alyssa Fanelli, Gauri Kulkarni, Ji Hye Seo, Paige Gilbride, Bing Wei, Bo Wang, Yanyan Liu, Fei Ma, Lin Zhou, Shuyang Wang, Xiaohua Qian, Zhiyong Xie, Polina Golland, Longlong Si, Yu Shrike Zhang, Xin Xie, Haiqing Bai   +24 more
wiley   +1 more source

An Environmental Sustainable Approach to Machine Learning, Training and Development

Sakarya University Journal of Computer and Information Sciences
Artificial intelligence has the potential to drive sustainability by minimizing the impact of machine learning (ML) development on the environment. However, many ML techniques, particularly ensemble methods like the Random Forest classifier, require ...
K Jegadeeswari, Rathipriya R
doaj   +1 more source

Machine Learning for Green Solvents: Assessment, Selection and Substitution

Advanced Science, EarlyView.
Environmental regulations have intensified demand for green solvents, but discovery is limited by Solvent Selection Guides (SSGs) that quantify solvent sustainability. Training a machine learning model on GlaxoSmithKline SSG, a database of sustainability metrics for 10,189 solvents, GreenSolventDB is developed. Integrated with Hansen solubility metrics,
Rohan Datta, Janhavi Nistane, Abhishek Sose, Harikrishna Sahu, Rampi Ramprasad   +4 more
wiley   +1 more source