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16081
Predicting the Evolution of Lung Squamous Cell Carcinoma In Situ Using Computational Pathology
Published 2025-04-01Get full text
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16082
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16083
Bioinformatics reveal macrophages marker genes signature in breast cancer to predict prognosis
Published 2021-01-01Get full text
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16084
Use of machine learning in predicting continuity of HIV treatment in selected Nigerian States.
Published 2025-01-01Get full text
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16085
Artificial neural networks in the outcome prediction of adjustable gastric banding in obese women.
Published 2010-10-01Get full text
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16086
Bayesian Joint Probability Approach for Post‐Processing Monthly Precipitation Prediction in Northwest Iran
Published 2024-08-01Get full text
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16087
Review of Pre-processing Techniques for Meteorological Satellite Data Assimilation in Numerical Prediction
Published 2024-03-01Get full text
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16088
Forest Loss and Susceptible Area Prediction at Sefwi Wiawso District (SWD), Ghana
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16089
A systematic review of computational simulation methods for predicting the toxicity of chemical compounds
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16090
A Study of Factors Influencing Chinese Design Students’ Adoption of AIGC Tools
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16091
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16092
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16093
Promises in Air‐Sea Fully Coupled Data Assimilation for Future Hurricane Prediction
Published 2018-12-01“…Abstract The recent article by Li and Toumi (2018, https://doi.org/10.1029/2018GL079677) published in Geophysical Research Letters explored the potential for improving tropical cyclone intensity forecasts by assimilating synthetic coastal surface currents from high‐frequency radar observations. …”
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16094
Machine learning for asphaltene polarizability: Evaluating molecular descriptors
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16095
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16096
Application of HRCT-based radiomics to predict interstitial lung disease for juvenile dermatomyositis
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16097
Fault Prediction of Hydropower Station Based on CNN-LSTM-GAN with Biased Data
Published 2025-07-01“…Finally, a dynamic multi-task training algorithm is proposed to ensure the convergence and training efficiency of the deep models. Experimental results show that compared with RNN, GRU, SVM, and threshold detection algorithms, the proposed fault prediction method improves the accuracy performance by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>5.5</mn><mo>%</mo></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4.8</mn><mo>%</mo></mrow></semantics></math></inline-formula>, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>7.8</mn><mo>%</mo></mrow></semantics></math></inline-formula>, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>9.3</mn><mo>%</mo></mrow></semantics></math></inline-formula>, with at least a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>160</mn><mo>%</mo></mrow></semantics></math></inline-formula> improvement in the fault recall rate.…”
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16098
Exercise Semantic Embedding for Knowledge Tracking in Open Domain
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16099
A learning experience design framework for multimodal learning in the early childhood
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16100