MDCKE: Multimodal deep-context knowledge extractor that integrates contextual information by Hyojin Ko, Joon Yoo, Ok-Ran Jeong

“…An ablation study further corroborated the contribution of each component, resulting in an approximately 6% enhancement in the F1-score across the datasets.…”
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ECP-IEM: Enhancing seasonal crop productivity with deep integrated models. by Ghulam Mustafa, Muhammad Ali Moazzam, Asif Nawaz, Tariq Ali, Deema Mohammed Alsekait, Ahmed Saleh Alattas, Diaa Salama AbdElminaam

“…The proposed model showed very good results in all datasets and showed significant improvement compared to baseline models. …”
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Hyperbolic Graph Convolutional Network Relation Extraction Model Combining Dependency Syntax and Contrastive Learning by Jinzhe Li

“…The experiments indicate that the proposed model in this paper can effectively enhance the performance of relation extraction on public datasets, especially achieving significantly higher precision on datasets with complex sentence structures compared to in-context learning.…”
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Utilizing Machine Learning-based Classification Models for Tracking Air Pollution Sources: A Case Study in Korea by Yelim Choi, Bogyeong Kang, Daekeun Kim

“…By analyzing multidimensional datasets containing a wide range of air pollutants, a machine learning approach has the potential to significantly improve air pollution management and facilitate source tracking. …”
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Mediastinal extension of amoebic liver abscess: A case report on the rare thoracic complication of Entamoeba histolytica by Gautam Jesrani, Jaspreet Kaur, Samiksha Gupta, Yuvraj Singh Cheema, Prashant Ahlawat

“…An ultrasound-guided pigtail catheter was manipulated and placed at the site of thoracic communication. …”
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Feature selection in single-cell RNA sequencing data: a comprehensive evaluation by Petros Paplomatas, Konstantinos Lazaros, Georgios N. Dimitrakopoulos, Aristidis Vrahatis

“…Our comprehensive evaluation across five diverse scRNA-seq datasets demonstrates that although some methods show consistent performance, the technique should be chosen according to specific datasets for obtaining optimal results. …”
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AI-Based Screening Method for Early Identification of Invasive Ductal Carcinoma in Breast Cancer by Dominik Jánošík, Sila Yavuz

“…To achieve this, we utilized a deep learning neural network algorithm, employing histopathological microscopic datasets and histological microscopic images from 124 and 576 patients with ductal carcinoma of the breast, respectively. …”
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Investigation of hemostasis by thromboelastography in the patient with liver cirrhosis (Clinical case) by Ye. L. Bulanova, A. Yu. Bulanov, D. S. Gatsolayeva

“…Intravenous infusion therapy required installation of central venous catheter, that was complicated by catheter bleeding. …”
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Multiomics-based assessment of the impact of airflow on diverse plant callus cultures by June-Sik Kim, Muneo Sato, Mikiko Kojima, Muchamad Imam Asrori, Yukiko Uehara-Yamaguchi, Yumiko Takebayashi, Thi Nhung Do, Thi Yen Do, Kieu Oanh Nguyen Thi, Hitoshi Sakakibara, Keiichi Mochida, Shinjiro Ogita, Masami Yokota Hirai

“…This study presents multiomics datasets from callus cultures of tobacco (Nicotiana tabacum), rice (Oryza sativa), and two bamboo species (Phyllostachys nigra and P. bambusoides). …”
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Unraveling multimodality of digital health records by comparing mortality trajectories of diagnoses of diseases from over 12 million patients. by Hyojung Paik

“…Although a substantial sequence of diagnostic processes is shared between USSID and NISK, the multimodality of these two datasets highlights different diagnoses preceded by fatal outcomes. …”
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Exploiting question-answer framework with multi-GRU to detect adverse drug reaction on social media by Jiao-huang Luo, Ai-hua Yang

“…Our method achieved F1-scores of 81.3% and 73.3% on the two datasets, respectively, while consistently maintaining a higher recall.…”
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Hydrological performance of gridded meteorological products in Peruvian Altiplano basins by Efrain Lujano, Renny Daniel Diaz, Rene Lujano, Miguel Sanchez-Delgado, Apolinario Lujano

“…ABSTRACT Gridded meteorological datasets represent a valuable alternative for hydrometeorological applications, especially in areas with limited ground observations. …”
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Identifying relevant EEG channels for subject-independent emotion recognition using attention network layers by Camilo E. Valderrama, Camilo E. Valderrama, Anshul Sheoran

“…With the growing use of deep learning in emotion recognition, incorporating attention mechanisms can help uncover these shared predictive patterns.MethodsThis study explores this method by applying attention mechanism layers to identify EEG channels that are relevant for predicting emotions in three independent datasets (SEED, SEED-IV, and SEED-V). ResultsThe model achieved average accuracies of 79.3% (CI: 76.0-82.5%), 69.5% (95% CI: 64.2-74.8%) and 60.7% (95% CI: 52.3-69.2%) on these datasets, revealing that EEG channels located along the head circumference, including Fp1, Fp2, F7, F8, T7, T8, P7, P8, O1, and O2, are the most crucial for emotion prediction. …”
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A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits. by Dennis Khodasevich, Nina Holland, Lars van der Laan, Andres Cardenas

“…We gathered publicly available DNAm datasets to generate i) a novel childhood epigenetic clock, ii) a reconstructed Hannum adult blood clock, and iii) as a proof of concept, a predictor of polybrominated biphenyl exposure using the three developmental methodologies. …”
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AMEND 2.0: module identification and multi-omic data integration with multiplex-heterogeneous graphs by Samuel S. Boyd, Chad Slawson, Jeffrey A. Thompson

“…AMEND was applied to two real-world multi-omic datasets: renal cell carcinoma data from The cancer genome atlas and an O-GlcNAc Transferase knockout study. …”
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Monte Carlo Algorithm For Matrices in Solving Systems of Linear Equations, Determinants, Inverse, Eigen Values, and Eigenvectors. by Bamwine, Delik

“…Monte Carlo methods, which are based on statistical sampling, exhibit many attractive properties in dealing with large volumes of datasets, including fast approximated results, memory efficiency, reduced data accesses, natural parallelism, and inherent fault tolerance. …”
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Phages as potential life-saving therapeutic option in the treatment of multidrug-resistant urinary tract infections by Beata Zalewska-Piątek, Michalina Nagórka

“…PT demonstrates significant potential in treating chronic and recurrent UTIs, also including catheter-associated infection by reducing bacterial biofilms, delaying catheter blockage, and enhancing antibiotic efficacy when used in combination. …”
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Optimising Access Surgery in Senior Haemodialysis Patients (OASIS): study protocol for a multicentre randomised controlled trial by Patrick WHE Vriens, Edith M Willigendael, Maarten A Lijkwan, Friedo W Dekker, Chava L Ramspek, Michiel W de Haan, Çaĝdaş Ünlü, Boudewijn DC Heggen, Koen E A van der Bogt, Marc H Hemmelder, Mickaël J C Hiligsmann, Magda M van Loon, Joris I Rotmans, Jan H M Tordoir, Geert Willem H Schurink, Maarten G J Snoeijs, Marijke J Molegraaf, Philippe WM Cuypers, Denise Nio, Cora H Arts, Jacobien C Verhave, Goos D Laverman, Aron S Bode, Marcel C Weijmer, Bas Govaert, Aaltje Y Adema, Gijs MJM Welten, Michel MPJ Reijnen, Marc JH Groeneveld, Hans S Brink, Jeroen B van der Net, Arno Kuijper, Hilde PE Peters, Roos C van Nieuwenhuizen, Rombout R Kruse, Yvonne C Schrama, Karina A de Groot, Karima Farhat

“…In addition, long-term complications associated with arteriovenous grafts and central venous catheters may be less relevant when considering the limited life expectancy of these patients. …”
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Advances in machine learning applications to resource technology for organic solid waste by Hongzhi MA, Yichan LIU, Jihua ZHAO, Fan FEI, Ming GAO, Qunhui WANG

“…These include issues related to data quality, such as missing or incomplete datasets, and the generalization ability of ML models across different treatment scenarios. …”
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InceptionDTA: Predicting drug-target binding affinity with biological context features and inception networks by Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi

“…We evaluate InceptionDTA across a range of benchmark datasets commonly used in drug-target binding affinity prediction. …”
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