Investigation of the effects of different denture base fabrication techniques and hard relining resin materials on the fixation of immediate provisional hybrid prosthesis to titani... by Burcu Kanat-Ertürk, Cansu Akarsu, Önjen Tak

“…This study aimed to investigate the effects of different denture base fabrication techniques and hard relining resins on the fixation of IPHPs to titanium cylinders using a push-out test, and observe the failure types. …”
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Teachers’ team innovativeness in TALIS 2018: An empirical and simulation study using glmmLasso for multilevel data by Miryeong Koo, Jin Eun Yoo

“…To address the multilevel structure of the data and perform comprehensive variable selection, we employed glmmLasso—a penalized regression technique that integrates generalized linear mixed models with LASSO penalties. …”
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Comparative Meta-Analysis of Recurrence Rates in Classical vs. Modified Limberg Flap Techniques for Pilonidal Sinus Disease Surgery: Evidence for Enhanced Efficacy by Dietrich Doll, Matthias Maak, Theo Hackmann, Christina Oetzmann von Sochaczewski, Myriam Braun-Münker, PiloNERDs International

“…Conclusion: This meta-analysis, which focused on recurrence rates associated with Limberg flap variants and analyzed data from 16,588 patients, shows that the modified Limberg flap technique effectively reduces the risk of recurrence compared to the already low recurrence rate associated with the classical Limberg flap. …”
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Survey of Deep Learning and Machine Learning Approaches for Major Depressive Disorder Detection Using EEG Data by Sumathi Balakrishnan, Raja Kumar Murugesan, Eng Lye Lim, Amna Faisal, Humaira Ashraf

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Investigating the Potential of Deep Learning Approaches in the Reconstruction of VNIR-SWIR Hyperspectral Data From Multispectral Imagery by Michael Alibani, Martina Pastorino, Gabriele Moser, Nicola Acito

“…This study, which aims to simulate data with high spectral and spatial resolution, explores the use of attention-based spectral reconstruction (SR) techniques, specifically MST++, MIRNet, AWAN, and Restormer, to derive HS data in the visible near infrared (VNIR) and short-wave infrared (SWIR) from MS imagery. …”
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Introduction to the usage of open data from the Large Hadron Collider for computer scientists in the context of machine learning by Timo Saala, Matthias Schott

“…As all machine learning techniques depend on the availability and comprehensibility of extensive data, clear data descriptions and commonly used data formats are prerequisites for successful collaboration. …”
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Burst Localisation in Water Pressurised Pipelines Combining Numerical Data Generation and ANN Transient Signal Processing by Andrea Menapace, Maurizio Tavelli, Daniele Dalla Torre, Maurizio Righetti

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Leveraging Artificial Intelligence and Data Science for Integration of Social Determinants of Health in Emergency Medicine: Scoping Review by Ethan E Abbott, Donald Apakama, Lynne D Richardson, Lili Chan, Girish N Nadkarni

“…These efforts aim to harness SDOH data optimally, enhancing patient care and mitigating health disparities. …”
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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…<b>Objectives</b>: The aim of this study is to evaluate and enhance the predictive capabilities of machine learning models for SSIs by assessing the effects of feature selection, resampling techniques, and hyperparameter optimization. …”
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Feedforward control with sampled-data polynomial based on triangle hold for track seek of hard disk drive by Kazuho IGARASHI, Ryo IGARASHI, Takenori ATSUMI, Shigeyuki NAKADAI

“…This research proposes feedforward control techniques aimed at reducing the seek time in hard disk drives (HDDs). …”
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Mining social media data to inform public health policies: a sentiment analysis case study by Suzana N. Russell, Lila Rao-Graham, Maurice McNaughton

“…This type of analysis can be useful to the health community and more generally to governments, as it allows for a more scientific assessment of public response to public health intervention techniques in real time. This study contributes to the emerging discourse on the integration of nontraditional data into public health policy-making, highlighting the growing potential for the use of these novel analytic techniques in addressing complex public health challenges.…”
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Comparative and Interpretative Analysis of CNN and Transformer Models in Predicting Wildfire Spread Using Remote Sensing Data by Yihang Zhou, Ruige Kong, Zhengsen Xu, Linlin Xu, Sibo Cheng

“…Abstract Facing the escalating threat of global wildfires, numerous computer vision techniques using remote sensing data have been applied in this area. …”
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Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data by Ailing Zhang, Haobo Zhang

“…Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and reduce both individual and societal costs. This study aimed to develop predictive models for depression in young adults using machine learning (ML) techniques and longitudinal data from the Beck Depression Inventory, structural MRI (sMRI), and resting-state functional MRI (rs-fMRI). …”
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Algorithms and tools for data-driven omics integration to achieve multilayer biological insights: a narrative review by Aurelia Morabito, Giulia De Simone, Roberta Pastorelli, Laura Brunelli, Manuela Ferrario

“…The high-throughput nature of omics platforms introduces issues such as variable data quality, missing values, collinearity, and dimensionality. …”
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A Methodological and Structural Review of Parkinson&#x2019;s Disease Detection Across Diverse Data Modalities by Abu Saleh Musa Miah, Taro Suzuki, Jungpil Shin

“…To address these gaps, this study presents a comprehensive review of PD recognition systems across diverse data modalities, including Magnetic Resonance Imaging (MRI), gait-based pose analysis, gait sensory data, handwriting analysis, speech test data, Electroencephalography (EEG), and multimodal fusion techniques. …”
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Big Earth data processing using machine learning for integrated mapping of the dead sea fault, Jordan by Polina Lemenkova

“…GIS applications encourage geological prospective modeling by visualizing data aimed at the prognosis of mineral resources. …”
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Big Earth data processing using machine learning for integrated mapping of the dead sea fault, Jordan by Polina Lemenkova

“…GIS applications encourage geological prospective modeling by visualizing data aimed at the prognosis of mineral resources. …”
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Long COVID Discourse in Canada, the United States, and Europe: Topic Modeling and Sentiment Analysis of Twitter Data by Ahmed Ghassan Tawfiq AbuRaed, Emil Azuma Prikryl, Giuseppe Carenini, Naveed Zafar Janjua

“…ObjectiveThis study aimed to investigate people’s perceptions and sentiments around long COVID in Canada, the United States, and Europe, by analyzing English-language tweets from these regions using advanced topic modeling and sentiment analysis techniques. …”
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Surgical Strategies in the Management of Raynaud's Phenomenon: Comparative Analysis of Trends and Effectiveness Incorporating New Clinical Data by Aleksandra Cygnarowicz, Mariola Turemka, Negar Hosseinnejad, Karolina Sacher, Aneta Klaudia Wojtas, Krystyna Zabojska, Mikołaj Biskupski, Urszula Korotko, Kinga Witowska, Aneta Mandziuk

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OPC-UA in artificial intelligence: a systematic review of the integration of data mining and NLP in industrial processes by Velesaca Henry O., Holgado-Terriza Juan A.

“…This systematic literature review explores the integration of OPC-UA with Data Mining and Natural Language Processing (NLP) techniques within industrial environments. …”
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