Results 221 to 230 of about 88,237 (314)

Machine Learning-Based Accurate Full-Sib Family Assignment in Sturgeon Using Whole-Genome Sequencing Data. [PDF]

Int J Mol Sci
Yan J, Li H, Dong T, Wang W, Yan X, Bai S, Song H, Hu H.   +7 more
europepmc   +1 more source

Early prediction of multiple organ failure for sepsis patients based on machine learning algorithms

Journal of Intelligent Medicine, EarlyView.
Abstract In recent years, there has been a notable rise in sepsis incidence leading to more multiple organ failure and higher mortality. The lack of effective treatments for sepsis highlights the importance of early prediction in preventing multiple organ failure. This study aimed to develop a model for the early prediction of multiple organ failure in
Runnan He, Nan Su, Yuqing Wang, Yulin Sun, Xin Weng, Tania Pereira, Chenggong Hu, Keliang Xie, Meijun Pang, Kuo Zhang, Chuanxiang Huang, Xiuyun Liu   +11 more
wiley   +1 more source

Use of Machine Learning Techniques for Fertilization Traceability Discrimination via Core Quality Indicators of Korla Fragrant Pear Fruits. [PDF]

Foods
Zeng J, Wang H, Yu M, Chen Y, Bao J.
europepmc   +1 more source

Early prediction of acute kidney injury in traumatic and non‐traumatic rhabdomyolysis using an interpretable machine learning model: A multicenter study with external validation

Journal of Intelligent Medicine, EarlyView.
Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic ...
Chunli Liu, Jie Shi, Fengjuan Wang, Liang Ma, Huangang Hu, Li Zhang, Jie Song, Heng Jin, Dingwei Yang, Xiaoqin Guo, Haojun Fan, Qi Lv   +11 more
wiley   +1 more source

Application of an Electronic Nose for Early Detection of Tephritidae Infestation in Fruits. [PDF]

Insects
Anastasaki E, Psoma A, Crivelli M, Toufexi S, Giakoumaki MV, Milonas P.   +5 more
europepmc   +1 more source

Failure Investigation of Alloy 625 Sockolets After Prolonged Service in an Ammonia Cracker Unit

Materials and Corrosion, EarlyView.
The failure of the sockolets was caused by intergranular cracking and fracture. The thick and highly brittle nitrided layer formed intergranular surface cracks, which propagated along grain boundaries into the base alloy substrate due to the presence of brittle Cr‐rich carbides. ABSTRACT Several sockolets of Alloy 625 operating at 540°C in contact with
Kamlesh Chandra, N. Naveen Kumar, Niraj Kumar   +2 more
wiley   +1 more source

A lightweight machine learning approach for DDoS detection and classification. [PDF]

Sci Rep
Ebrahem O, Dowaji S, Alhammoud S.
europepmc   +1 more source

Machine Learning Assisted Prediction of Degradation Behavior of Poly(Lactic‐Co‐Glycolic Acid)

Materials Genome Engineering Advances, EarlyView.
Using a gradient boosting‐based machine learning model trained on 484 data points, this study predicts the degradation behavior of poly(lactic‐co‐glycolic acid) (PLGA) implants. Degradation time, molecular weight, and lactide/glycolide ratio were identified as key governing factors, enabling accurate prediction while reducing reliance on extensive ...
Shuai Wang, Long Chen, Kepeng Yang, Bowen Cheng, Yingpeng Wan, Bingyan Wang, Tao Sun, Xiangping Hao, Jingzhi Yang, Haijun Zhang, Lei Wang, Lu‐Ning Wang   +11 more
wiley   +1 more source

Improving the estimation accuracy of rice leaf protein nitrogen using data augmentation, explainable machine learning, and UAV hyperspectral imagery. [PDF]

Front Plant Sci
Peng Y, Tu Y, Xu Y, Zhong W, Li Z, Liang J, Huang J.   +6 more
europepmc   +1 more source

Heart Disease Prediction Using Extended KNN(E-KNN)

International Journal of Advanced Trends in Computer Science and Engineering, 2020
openaire   +1 more source