From parental education to under-5 mortality: how antenatal care and hand hygiene mediate the pathway mechanisms by Tapas Mazumder, Itismita Mohanty, Danish Ahmad, Theo Niyonsenga

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A Hybrid Machine Learning Framework for Soccer Match Outcome Prediction: Incorporating Bivariate Poisson Distribution by Chen Zhong An

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MODEL PENEMUAN KONSEP BERBASIS TEKS PADA PEMBELAJARAN SASTRA by Nazla Maharani Umaya

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Compilation and analysis of thaw settlement test results: implications for prediction tools and stress–strain characterization in permafrost by Z. Mohammadi, J. L. Hayley

“…The dataset is accessible at <a href="https://doi.org/10.5281/zenodo.15192404">https://doi.org/10.5281/zenodo.15192404</a> (Mohammadi and Hayley, 2024c), and the results presented in this paper are based on version 1.2.1 of the dataset. …”
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Prediction of the 3D cancer genome from whole-genome sequencing using InfoHiC by Yeonghun Lee, Sung-Hye Park, Hyunju Lee

“…In addition, we provide trained models for cancer Hi-C prediction from WGS at https://github.com/dmcb-gist/InfoHiC , uncovering the impacts of SVs in cancer patients and revealing novel therapeutic targets.…”
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Reducing Mesh Dependency in Dataset Generation for Machine Learning Prediction of Constitutive Parameters in Sheet Metal Forming by Dário Mitreiro, Pedro A. Prates, António Andrade-Campos

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Accuracy of genome-enabled polygenic risk score prediction of cruciate ligament rupture risk in the Labrador Retriever by Benjamin Miranda, Mehdi Momen, Susannah J. Sample, Peter Muir

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Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity. by Alexandre Guet-McCreight, Frank Mazza, Thomas D Prevot, Etienne Sibille, Etay Hay

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Evidence-based dust exposure prediction and/or control tools in occupational settings: A scoping review protocol. by Gebisa Guyasa Kabito, Yonatal Tefera, Chandnee Ramkissoon, Sharyn Gaskin

“…In recent decades, evidence-based tools supporting exposure modelling and control banding have been developed to aid in predicting and/or controlling occupational exposure to various contaminants. …”
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Machine learning for outcome prediction in patients with non-valvular atrial fibrillation from the GLORIA-AF registry by Martha Joddrell, Wahbi El-Bouri, Stephanie L. Harrison, Menno V. Huisman, Gregory Y. H. Lip, Yalin Zheng, GLORIA-AFinvestigators

“…Abstract Clinical risk scores that predict outcomes in patients with atrial fibrillation (AF) have modest predictive value. …”
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Machine Learning-Driven Prediction of Offshore Vessel Detention: The Role of Neural Networks in Port State Control by Zlatko Boko, Tatjana Stanivuk, Nenad Radanović, Ivica Skoko

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A Comprehensive Analysis of Imbalance Signal Prediction in the Japanese Electricity Market Using Machine Learning Techniques by Kaiyao Jiang, Yuji Yamada

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From rings to regions: modeling and mapping climate-driven timber production zones for Cyclocarya paliurus by integrating niche models and growth traits by Zijie Zhang, Zijie Zhang, Zhengyang Ye, Xulan Shang, Xulan Shang, Wanxia Yang, Wanxia Yang, Tongli Wang, Shengzuo Fang, Shengzuo Fang

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Remote Sensing Perspective on Monitoring and Predicting Underground Energy Sources Storage Environmental Impacts: Literature Review by Aleksandra Kaczmarek, Jan Blachowski

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Innovation indicators based on firm websites-Which website characteristics predict firm-level innovation activity? by Janna Axenbeck, Patrick Breithaupt

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The Effectiveness of Digital Animation–Based Multistage Education for Patients With Atrial Fibrillation Catheter Ablation: Randomized Clinical Trial by Xiaoyu Shi, Yijun Wang, Yuhong Wang, Jun Wang, Chen Peng, Siyi Cheng, Lingpeng Song, Rui Li, Fuding Guo, Zeyan Li, Shoupeng Duan, Xiaomeng Yang, Liping Zhou, Hong Jiang, Lilei Yu

“…This educational model effectively improves postoperative anxiety, depression, medication adherence, and quality of life in patients at 3 months post discharge. …”
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Hybrid machine learning for real-time prediction of edema trajectory in large middle cerebral artery stroke by Ethan Phillips, Odhran O’Donoghue, Yumeng Zhang, Panos Tsimpos, Leigh Ann Mallinger, Stefanos Chatzidakis, Jack Pohlmann, Yili Du, Ivy Kim, Jonathan Song, Benjamin Brush, Stelios Smirnakis, Charlene J. Ong, Agni Orfanoudaki

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Credit Risk Prediction Using Machine Learning and Deep Learning: A Study on Credit Card Customers by Victor Chang, Sharuga Sivakulasingam, Hai Wang, Siu Tung Wong, Meghana Ashok Ganatra, Jiabin Luo

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Predicting Resistance to Immunotherapy in Melanoma, Glioblastoma, Renal, Stomach and Bladder Cancers by Machine Learning on Immune Profiles by Guillaume Mestrallet

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Predicting fall risk in older adults: A machine learning comparison of accelerometric and non-accelerometric factors by Ana González-Castro, José Alberto Benítez-Andrades, Rubén González-González, Camino Prada-García, Raquel Leirós-Rodríguez

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