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Predictive modeling
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The process of neural stem cell (NSC) differentiation into neurons is crucial for the development of potential cell-centered treatments for central nervous system disorders. However, predicting, identifying, and anticipating this differentiation is complex. In this study, we propose the implementation of a convolutional neural network model for the predictable recognition of NSC fate, utilizing single-cell brightfield images.
7p
vithomson
02-07-2024
0
0
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This study seeks to introduce a more comprehensive assessment method than previous endeavors, particularly concerning the bond strength of FRP bars with various surface types within concrete, spanning normal, high-strength, and ultra-high-strength concrete.
16p
vithomson
02-07-2024
0
0
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This study focuses on developing the predicted models of materials removal rate and tool wear rate by utilizing the response surface method (RSM) for the machining of SKD61 steel by EDM process with adding tungsten compound powder.
14p
vithomson
02-07-2024
0
0
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Part 1 of ebook "Applied predictive modeling" provides readers with contents including: Chapter 1 - Introduction; Chapter 2 - A short tour of the predictive modeling process; Chapter 3 - Data pre-processing; Chapter 4 - Overfitting and model tuning; Chapter 5 - Measuring performance in regression models; Chapter 6 - Linear regression and its cousins; Chapter 7 - Nonlinear regression models; Chapter 8 - Regression trees and rule-based models; Chapter 9 - A Summary of solubility models; Chapter 10 - Case study compressive strength of concrete mixtures;...
251p
daonhiennhien
03-07-2024
2
1
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Part 2 of ebook "Applied predictive modeling" provides readers with contents including: Chapter 11 - Measuring performance in classification models; Chapter 12 - Discriminant analysis and other linear classification models; Chapter 13 - Nonlinear classification models; Chapter 14 - Classification trees and rule-based models; Chapter 15 - A Summary of grant application models; Chapter 16 - Remedies for severe class imbalance; Chapter 17 - Case study job scheduling; Chapter 18 - Measuring predictor importance; Chapter 19 - An introduction to feature selection; Chapter 20 - Factors that can af...
344p
daonhiennhien
03-07-2024
1
1
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Part 2 of ebook "Artificial intelligence for fashion: How AI is revolutionizing the fashion industry" provides readers with contents including: Chapter 6 - Data science and subscription services; Chapter 7 - Predictive analytics and size recommendations; Chapter 8 - Generative models as fashion designers; Chapter 9 - Data mining and trend forecasting; Chapter 10 - Deep learning and demand forecasting; Chapter 11 - Robotics and manufacturing; Chapter 12 - Democratization and impacts of AI;...
121p
daonhiennhien
03-07-2024
1
1
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Part 1 of ebook "The elements of statistical learning: Data mining, inference, and prediction (Second edition)" provides readers with contents including: Chapter 1 - Introduction; Chapter 2 - Overview of supervised learning; Chapter 3 - Linear methods for regression; Chapter 4 - Linear methods for classification; Chapter 5 - Basis expansions and regularization; Chapter 6 - Kernel smoothing methods; Chapter 7 - Model assessment and selection; Chapter 8 - Model inference and averaging; Chapter 9 - Additive models, trees, and related methods;...
355p
daonhiennhien
03-07-2024
2
1
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Part 2 of ebook "The elements of statistical learning: Data mining, inference, and prediction (Second edition)" provides readers with contents including: Chapter 10 - Boosting and additive trees; Chapter 11 - Neural networks; Chapter 12 - Support vector machines and flexible discriminants; Chapter 13 - Prototype methods and nearest-neighbors; Chapter 14 - Unsupervised learning; Chapter 15 - Random forests; Chapter 16 - Ensemble learning; Chapter 17 - Undirected graphical models; Chapter 18 - High-dimensional problems p ≫ N;...
409p
daonhiennhien
03-07-2024
4
1
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In recent times, the phase field method is a robust simulation tool that can predict crack formation and propagation in structures. In brittle and quasi-brittle materials, the strain tensor is decomposed into negative and positive parts corresponding to the compression and tension behaviors when the structure is loaded.
14p
viwalton
02-07-2024
1
1
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A truss model supplementing the concrete contribution is introduced in this paper to predict the shear strength of concrete beams reinforced with various types of FRP bars. The contributions from truss and direct strut mechanisms are considered in the analytical model. The truss model which has struts at various angles considering concrete contribution is derived in this paper.
13p
viwalton
02-07-2024
2
1
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In this study, we explore the potential of graph neural networks (GNNs), in combination with transfer learning, for the prediction of molecular solubility, a crucial property in drug discovery and materials science. Our approach begins with the development of a GNN-based model to predict the dipole moment of molecules.
8p
viwalton
02-07-2024
3
1
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The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC).
14p
vishanshan
27-06-2024
1
1
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The objective of this study was to externally validate the KELIM (rate of elimination of CA-125) score in patients with high-grade serous ovarian cancer (HGSC) undergoing NACT and explore its relation to the completeness of IDS and survival.
8p
vishanshan
27-06-2024
2
1
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Ferroptosis has important value in cancer treatment. It is signifcant to explore the new ferroptosis-related lncRNAs prediction model in Hepatocellular carcinoma (HCC) and the potential molecular mechanism of ferroptosis-related lncRNAs.
15p
vishanshan
27-06-2024
1
1
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Paclitaxel is commonly used as a second-line therapy for advanced gastric cancer (AGC). The decision to proceed with second-line chemotherapy and select an appropriate regimen is critical for vulnerable patients with AGC progressing after first-line chemotherapy.
9p
vishanshan
27-06-2024
2
1
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To predict pathological complete response (pCR) in patients receiving neoadjuvant immunochemotherapy (nICT) for esophageal squamous cell carcinoma (ESCC), we explored the factors that influence pCR after nICT and established a combined nomogram model.
12p
vishanshan
27-06-2024
2
1
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Based on the quantitative and qualitative features of CT imaging, a model for predicting the invasiveness of ground-glass nodules (GGNs) was constructed, which could provide a reference value for preoperative planning of GGN patients.
12p
vishanshan
27-06-2024
1
1
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To establish and validate a predictive model combining pretreatment multiparametric MRI-based radiomic signatures and clinical characteristics for the risk evaluation of early rapid metastasis in nasopharyngeal carcinoma (NPC) patients.
12p
vishanshan
27-06-2024
2
1
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This research aimed to create a robust signature with hypoxia-related genes to predict the prognosis of breast cancer patients. The function of hypoxia genes was further studied through cell line experiments.
12p
vishanshan
27-06-2024
3
1
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Clear cell renal cell carcinoma (ccRCC) is associated with a high prevalence of cancer-related deaths. This study aims to develop an efficient nomogram model for stratifying and predicting the survival of ccRCC patients based on tumor stage.
13p
vishanshan
27-06-2024
1
1
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