Machine learningMRIProstate cancerRadiomicsThe Author(s) 2024.Background: To build machine learning predictive models for surgical risk assessment of extracapsular extension (ECE) in patients with prostate cancer (PCa) before radical prostatectomy; and to compare the use of decision curve analysis (...
In contrast, machine learning algorithms can easily handle hundreds of attributes (parameters), and they are capable of detecting and utilizing the interactions among these numerous attributes, which makes this field of medicine particularly interesting for machine learning applications. Our hypothesis was...
Unlike unsupervised PCA, a trained machine learning algorithm can rapidly classify a new analyte from a data set of raw Raman spectra and provide a direct readout. Nevertheless, machine learning algorithms has seen limited applications in solving food science related problems, coupled with advanced ...
This study aims to conduct cluster analysis of the data from the implementation of competency tests using Machine Learning techniques through the application of Principal Component Analysis (PCA) and K-Means Algorithm, through several stages in the form of data collection, data cleaning, data ...
Techniques like Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE) and UMAP [92] help in simplifying models, reducing computation time, and mitigating the curse of dimensionality while preserving essential relationships in the data. This key feature associated to ...
This early prediction, moreover, can be helpful in controlling the symptoms of the disease as well as the proper treatment of disease. Machine learning approaches can be used in the prediction of chronic diseases, such as kidney and heart diseases, by developing the classification models. In ...
The validation step was conducted on 80% of the total dataset and the remaining (randomly selected) 20% was used in the test step [27]. A dimensionality reduction step was conducted before the validation step, and this used principal component analysis (PCA). The minimum number of model ...
coatings Article Application of Machine Learning to Solid Particle Erosion of APS-TBC and EB-PVD TBC at Elevated Temperatures Yuan Liu 1, Ravi Ravichandran 1, Kuiying Chen 2,* and Prakash Patnaik 2 Citation: Liu, Y.; Ravichandran, R.; Chen, K.; Patnaik, P. Application of Machine ...
1.Wikipedia-PCA:https://en.wikipedia.org/wiki/Principal_component_analysis 2.An intuitive explanation of PCA(provided by Jesse Wu):http://mengnote.blogspot.com/2013/05/an-intuitive-explanation-of-pca.html 3.教科書:資料科學家手冊 4.Gram_Schmidt Process:https://en.wikipedia.org/wiki/Gram–...
For the first time, an attempt has been made in this study to adapt machine learning algorithms for predicting women with malnutrition using Bangladesh Demographic Health Survey (BDHS), 2014. The hypothesis of this study is to propose a better system/combination through a multinomial logistic ...