Clinical Validation of a Machine Learning-Based Biomarker Signature to Predict Response to Cytotoxic Chemotherapy Alone or Combined with Targeted Therapy in Metastatic Colorectal C... by Duilio Pagano, Vincenza Barresi, Alessandro Tropea, Antonio Galvano, Viviana Bazan, Adele Caldarella, Cristina Sani, Gianpaolo Pompeo, Valentina Russo, Rosa Liotta, Chiara Scuderi, Simona Mercorillo, Floriana Barbera, Noemi Di Lorenzo, Agita Jukna, Valentina Carradori, Monica Rizzo, Salvatore Gruttadauria, Marco Peluso

“…The study will involve dividing patients into training and validation sets to develop and test the models, avoiding overfitting. Various machine learning algorithms, like random survival forest and neural networks, will be integrated to develop a highly accurate and stable predictive model. …”
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Applying Extensions of Evidence Theory to Detect Frauds in Financial Infrastructures by Luigi Coppolino, Salvatore D'Antonio, Valerio Formicola, Luigi Romano

“…In order to solve these flaws, a number of amendments and extensions of the initial DS model have been proposed in literature. In this work, we present a Fraud Detection System that classifies transactions in a Mobile Money Transfer infrastructure by using the data fusion algorithms derived from these new models. …”
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Solving the RNA design problem with reinforcement learning. by Peter Eastman, Jade Shi, Bharath Ramsundar, Vijay S Pande

“…Our agent uses a novel graph convolutional architecture allowing a single model to be applied to arbitrary target structures of any length. …”
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Study on the Trajectory Planning Method for High Bearing Capacity of Joint Manipulator by Tang Runzhi, Li Tiejuni, Yang Dongi

“…Aiming at the problem of low deadweight ratio of load in joint manipulator，two trajectory planning methods to improve the bearing capacity of the joint manipulator are proposed. …”
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Keyword spotting system for broadcast news by ZHANG Peng-yuan, SHAO Jian, ZHAO Qing-wei, YAN Yong-hong

“…A two-step keyword spotting strategy was presented.This strategy allowed to change keyword list conven-iently.Different from the previous systems,search space was generated based on all Chinese syllables,not specifically for keywords.Phoneme recognition was performed without any lexical constraints.With 1-best phoneme sequence and keyword list,which generated keyword hypotheses.At last,two confidence measures were introduced adopted in the sys-tem: one based on acoustic model and the other based on phoneme lattice.For a decoded speech frame aligned to an HMM state,the acoustic confidence was calculated.The lattice confidence made use of phoneme lattices generated by a phoneme recognizer.These two confidence measures were combined using a weighting factor to obtain a hybrid confi-dence as they had different dynamic scales.Experiments show that the proposed algorithms significantly improve the system performance on the broadcast news task.…”
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Keyword spotting system for broadcast news by ZHANG Peng-yuan, SHAO Jian, ZHAO Qing-wei, YAN Yong-hong

“…A two-step keyword spotting strategy was presented.This strategy allowed to change keyword list conven-iently.Different from the previous systems,search space was generated based on all Chinese syllables,not specifically for keywords.Phoneme recognition was performed without any lexical constraints.With 1-best phoneme sequence and keyword list,which generated keyword hypotheses.At last,two confidence measures were introduced adopted in the sys-tem: one based on acoustic model and the other based on phoneme lattice.For a decoded speech frame aligned to an HMM state,the acoustic confidence was calculated.The lattice confidence made use of phoneme lattices generated by a phoneme recognizer.These two confidence measures were combined using a weighting factor to obtain a hybrid confi-dence as they had different dynamic scales.Experiments show that the proposed algorithms significantly improve the system performance on the broadcast news task.…”
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A brain-inspired memory transformation based differentiable neural computer for reasoning-based question answering by Yao Liang, Yao Liang, Yuwei Wang, Yuwei Wang, Hongjian Fang, Hongjian Fang, Feifei Zhao, Yi Zeng, Yi Zeng, Yi Zeng, Yi Zeng, Yi Zeng

“…The Differentiable Neural Computer (DNC) model, despite addressing these issues to some extent, still faces challenges such as algorithmic complexity, slow convergence, and limited robustness. …”
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Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Results: The regression tree model outperformed all 9 metalearner models. Tree results suggested group-based PT yielded the largest improvement in mean WOMAC score. …”
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Machine Learning Applications in Road Pavement Management: A Review, Challenges and Future Directions by Tiago Tamagusko, Matheus Gomes Correia, Adelino Ferreira

“…We discuss the limitations of conventional PMS and explore how Artificial Intelligence (AI) algorithms can overcome these shortcomings by improving the accuracy of pavement condition assessments, enhancing performance prediction, and optimizing maintenance and rehabilitation decisions. …”
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MC21 v.10 – coupled-radiation Monte Carlo transport solver with support for multiphysics simulations by Griesheimer David P., Gill Daniel F., Nease Brian R., Pavlou Andrew, Stedry Mark H., Thompson Jason T., Burke Paul E., Dobreff Peter S.

“…Over the past decade, the development of the MC21 Monte Carlo radiation transport solver has focused on extending the functionality of the code beyond static calculations of reactivity and reaction rate distributions, as well as improving accuracy, performance, and scalability. Notable improvements include enhanced interaction physics models, efficient model representation and tracking algorithms, support for coupled physics calculations using both in-line and externally coupled feedback modules, and the development of native visualization and results post-processing tools. …”
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Dual branch guided contrastive learning for unsupervised pedestrian re-identification by REN Hangjia, LIANG Fengmei

“…Finally, a contrastive learning module was proposed to perform contrastive learning on refined labels and improve the robustness of the model. The experimental results on the Market1501, DukeMTMC-ReID, and MSMT17 datasets validate the effectiveness of the proposed method.…”
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Diabetes-focused food recommender system (DFRS) to enabling digital health. by Esmael Ahmed, Mohammed Oumer, Medina Hassan

“…The integration of digital health technologies into diabetes management has shown the potential to improve patient outcomes by providing personalized dietary recommendations. …”
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Impact of imbalanced features on large datasets by Waleed Albattah, Rehan Ullah Khan

“…Distributed Gaussian (D-GA) and Distributed Poisson (D-PO) are found to be the most effective techniques, especially in improving Random Forest (RF) and SVM models. The deep learning experiments also show an improvement as such.…”
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Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis by Zhi-xiang Zhang, Yi-lin Cao, Chao Chen, Lin-yuan Wen, Yi-ding Ma, Bo-zhou Wang, Ying-zhe Liu

“…The modeling was performed based on a dataset consisting of 885 various compounds using linear and nonlinear algorithms. …”
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Assessing reading fluency in elementary grades: A machine learning approach by Gabriel Candido da Silva, Rodrigo Lins Rodrigues, Américo N. Amorim, Lieny Jeon, Emilia X.S. Albuquerque, Vanessa C. Silva, Vinícius F. da Silva, André L.A. Pinheiro, João P.J.R. Nunes, Suzana X.M.G. de Souza, Maxsuel S. Silva, Igor Mauro, Alexandre Magno Andrade Maciel

“…This study compares eleven widely used machine learning algorithms to identify the most accurate and comprehensive method for assessing children's reading fluency. …”
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Potassium Fulvate Alleviates Salinity and Boosts Oat Productivity by Modifying Soil Properties and Rhizosphere Microbial Communities in the Saline–Alkali Soils of the Qaidam Basin... by Jie Wang, Xin Jin, Xinyue Liu, Yunjie Fu, Kui Bao, Zhixiu Quan, Chengti Xu, Wei Wang, Guangxin Lu, Haijuan Zhang

“…Structural equation modeling further showed that PF mitigates salinity chiefly by improving soil physicochemical properties (path coefficient = −0.77; <i>p</i> < 0.001), with microbial assemblages acting as key intermediaries. …”
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Review of Demand Response-based Optimal Scheduling of Electric and Thermal Integrated Energy Systems by Jingshan MO, Guangxian YAN, Na SONG, Mingyang YUAN

“…This study provides an overview of the current research status, classification of scheduling models, and model solution methods for demand response-based scheduling of electric and thermal integrated energy systems in recent years. …”
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Bottlenose dolphin identification using synthetic image-based transfer learning by Changsoo Kim, Byung-Yeob Kim, Dong-Guk Paeng

“…Despite recent developments in learning-based photo-ID algorithms, the lack of training data for these models has become a bottleneck for improving the accuracy of these algorithms. …”
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Simulation of Minefield Installation in a Video Game Engine by Maksym Maksymov, Oleksii Neizhpapa, Oleksandr Toshev, Maksym Kiriakidi

“…The first objective of this research is to improve damage prediction algorithms, enabling the simulation to more accurately estimate the consequences of ships passing through a minefield. …”
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Chronobiologically-informed features from CGM data provide unique information for XGBoost prediction of longer-term glycemic dysregulation in 8,000 individuals with type-2 diabetes... by Jamison H Burks, Leslie Joe, Karina Kanjaria, Carlos Monsivais, Kate O'laughlin, Benjamin L Smarr

“…These findings support the use of chronobiologically-inspired and explainable features to improve glucose prediction algorithms with relatively long time-horizons.…”
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