Results 91 to 100 of about 3,566,037 (267)

Machine learning aided meta-analysis of the impacts of non-biodegradable and biodegradable microplastics on soil microbial communities

Agriculture Communications
Microplastics (MPs) have emerged as significant pollutants in terrestrial ecosystems. However, their impacts on soil microbial communities remain poorly understood.
Wenwen Gong, Zongyu Wen, Gang Liang, Qingwei Bu, Xiaowei Liu, Anxiang Lu, Dongmei Geng   +6 more
doaj   +1 more source

Multi-test Decision Tree and its Application to Microarray Data Classification [PDF]

, 2014
Objective: The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the ...
Marcin Czajkowski, Czajkowski, Marcin, Grzes, Marek, Marek Grześ, Marek Kretowski, Kretowski, Marek   +5 more
core   +1 more source

Smart Bioinks for 4D Bioprinting: Requirements, Design, and Applications

Advanced Science, EarlyView.
Smart bioinks empower 4D‐bioprinted constructs to dynamically adapt and remodel in response to stimuli, effectively biomimicking native tissues. Artificial Intelligence (AI) and Machine Learning (ML) play a guiding role in their rational design by optimizing relevant properties.
Shangsi Chen, Jiahui Lai, Qiongjiao Zeng, Liangbin Zhou, Boguang Yang, Bin Zhang, Min Wang, Jiajing Zhou, Kieran Lau, Khoon S. Lim, Zhong Alan Li, Rocky S. Tuan   +11 more
wiley   +1 more source

Regularized regression outperforms trees for predicting cognitive function in the Health and Retirement Study

Machine Learning with Applications
Background: Generalized linear models have been favored in healthcare research due to their interpretability. In contrast, tree-based models, such as random forest or boosted trees, are often preferred in machine learning (ML) and commercial settings due
Kyle Masato Ishikawa, Deborah Taira, Joseph Keaweʻaimoku Kaholokula, Matthew Uechi, James Davis, Eunjung Lim   +5 more
doaj   +1 more source

Hyperparameters for the reaction time gradient-boosted regression tree model predicting the reaction time from the onset of the target word from the subset of correct hit responses.

Hyperparameters for the reaction time gradient-boosted regression tree model predicting the reaction time from the onset of the target word from the subset of correct hit responses.
Joseph Sollini (9221201), Jules M. Lebert (18389720), Carla S. Griffiths (18389717), Jennifer K. Bizley (3666442)   +3 more
core   +1 more source

Integrated Multi‐Omics Reveals Cellular States and Microenvironmental Remodeling in Coexisting DCIS and IDC

Advanced Science, EarlyView.
Coexisting DCIS and IDC samples are profiled using spatial transcriptomics, single‐cell RNA sequencing, and single‐cell DNA sequencing. Integrative multi‐omics analysis reveals distinct malignant epithelial and microenvironmental features between DCIS and IDC, which are further validated using Xenium and multiplex immunohistochemistry.
Ning Zhang, Tong Wan, Siyue Zhang, Yunzhen Jiang, Peng Su, Jixin Liu, Zhitong Chen, Jie Hao, Haoyu Wang, Bing Chen, Wenjing Zhao, Lijuan Wang, Tao Xing, Qihuang Zhang, Ulf Schmitz, Zhiyong Ding, Nicola Crosetto, Bingqiang Liu, Qifeng Yang   +18 more
wiley   +1 more source

Hyperparameters for the absolute reaction time gradient-boosted regression tree model that predicts the reaction time relative to the male talker type trial start time.

Hyperparameters for the absolute reaction time gradient-boosted regression tree model that predicts the reaction time relative to the male talker type trial start time.
Joseph Sollini (9221201), Jules M. Lebert (18389720), Carla S. Griffiths (18389717), Jennifer K. Bizley (3666442)   +3 more
core   +1 more source

Final Four biomarkers from boosted regression.

, 2016
Final Four biomarkers from boosted regression.
Denny Meyer (828573), Julie A. Pasco (223870), Michael Berk (343706), Lana J. Williams (657175), Felice N. Jacka (343702), Joanna F. Dipnall (2157217), Seetal Dodd (828571)   +6 more
core   +1 more source

Single‐Cell Transcriptomic Profiling Identifies B Cell‐Intrinsic Dysregulation of Sphingolipid Biosynthesis and Could Be Improved by Inhibiting UGCG in Primary Immune Thrombocytopenia

Advanced Science, EarlyView.
This study generates the single‐cell atlas of pathogenic B‐cell subset Bc‐5 in ITP. It identifies RUNX3 as a key survival regulator and uncovers sphingolipid‐driven metabolic reprogramming, validating UGCG inhibition as a therapeutic candidate and building a valuable resource for ITP mechanistic and therapeutic exploration.
Dongmei Luo, Yanxia Zhan, Lili Ji, Pengcheng Xu, Pu Chen, Hao Pang, Yunan Ling, Fanli Hua, Xibing Zhuang, Hao Chen, Yunfeng Cheng   +10 more
wiley   +1 more source

Hyperparameters for the absolute reaction time gradient-boosted regression tree model that predicts the reaction time relative to the female talker type trial start time.

Hyperparameters for the absolute reaction time gradient-boosted regression tree model that predicts the reaction time relative to the female talker type trial start time.
Joseph Sollini (9221201), Jules M. Lebert (18389720), Carla S. Griffiths (18389717), Jennifer K. Bizley (3666442)   +3 more
core   +1 more source