Robotic Versus Laparoscopic Liver Resection: A Nationwide Propensity Score Matched Analysis by Gabriela Pilz da Cunha, MD, Jasper P. Sijberden, MD, PhD, Susan van Dieren, PhD, Paul Gobardhan, MD, PhD, Daan J. Lips, MD, PhD, Türkan Terkivatan, MD, PhD, Hendrik A. Marsman, MD, PhD, Gijs A. Patijn, MD, PhD, Wouter K. G. Leclercq, MD, PhD, Koop Bosscha, MD, PhD, J. Sven D. Mieog, MD, PhD, Peter B. van den Boezem, MD, PhD, Maarten Vermaas, MD, PhD, Niels F. M. Kok, MD, PhD, Eric J. T. Belt, MD, PhD, Marieke T. de Boer, MD, PhD, Wouter J. M. Derksen, MD, PhD, Hans Torrenga, MD, PhD, Paul M. Verheijen, MD, PhD, Steven J. Oosterling, MD, PhD, Arjen M. Rijken, MD, PhD, Marielle M. E. Coolsen, MD, PhD, Mike S. L. Liem, MD, PhD, T.C. Khé Tran, MD, PhD, Michael F. Gerhards, MD, PhD, Vincent Nieuwenhuijs, MD, PhD, Mohammad Abu Hilal, MD, PhD, Marc G. Besselink, MD, PhD, Ronald M. van Dam, MD, PhD, Jeroen Hagendoorn, MD, PhD, Rutger-Jan Swijnenburg, MD, PhD, for the Dutch Hepatobiliary Audit Group

“…Sensitivity analyses assessed the impact of the learning curve (≥50 procedures for LLR and ≥25 procedures for RLR), concurrent noncholecystectomy operations, high-volume centers, and conversion on outcomes. …”
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TAME 2.0: expanding and improving online data science training for environmental health research by Alexis Payton, Alexis Payton, Alexis Payton, Elise Hickman, Elise Hickman, Elise Hickman, Jessie Chappel, Jessie Chappel, Jessie Chappel, Kyle Roell, Kyle Roell, Lauren E. Koval, Lauren E. Koval, Lauren A. Eaves, Lauren A. Eaves, Chloe K. Chou, Chloe K. Chou, Chloe K. Chou, Allison Spring, Allison Spring, Sarah L. Miller, Sarah L. Miller, Sarah L. Miller, Oyemwenosa N. Avenbuan, Oyemwenosa N. Avenbuan, Oyemwenosa N. Avenbuan, Rebecca Boyles, Rebecca Boyles, Paul Kruse, Cynthia V. Rider, Grace Patlewicz, Caroline Ring, Cavin Ward-Caviness, David M. Reif, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Rebecca C. Fry, Rebecca C. Fry, Rebecca C. Fry, Julia E. Rager, Julia E. Rager, Julia E. Rager, Julia E. Rager

“…Training topics were prioritized based upon ongoing engagement with trainees, professional colleague feedback, and emerging topics in the field of environmental health research (e.g., artificial intelligence and machine learning). TAME 2.0 is a significant expansion upon the original TAME training resource pilot. …”
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AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders by Diego D. Díaz-Guerra, Marena de la C. Hernández-Lugo, Yunier Broche-Pérez, Carlos Ramos-Galarza, Ernesto Iglesias-Serrano, Zoylen Fernández-Fleites

“…The protocol utilizes AI to enhance diagnostic accuracy by analyzing data from these tests and supplementing observations made by researchers.Anticipated resultsThe AI-assisted protocol offers several advantages, including a thorough and customized evaluation of neurocognitive functions. It employs machine learning algorithms to analyze test results, generating an individualized neurocognitive profile that highlights patterns and trends useful for clinical decision-making. …”
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Cadmium and selenium blood levels in association with congestive heart failure in diabetic and prediabetic patients: a cross-sectional study from the national health and nutrition... by Renyue Ji, Haisheng Wu, Hongli Lin, Yang Li, Yumeng Shi

“…Logistic regression, weighted quantile sum (WQS), and Bayesian kernel machine learning (BKMR) models were employed to investigate the association between exposure to mixtures of five heavy metals and the odds of having CHF in individuals with diabetes and prediabetes. …”
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Pengembangan media pembelajaran matematika berbasis Android menggunakan Augmented Reality pada materi jaring-jaring kubus dan balok by Ikmawati Ikmawati, Ariantje Dimpudus, Kevin Ely Asar Greas, Muhammad Ramadani, Yeisha Lorry Ega Pakpahan, Nur Insan Ramadhani

“…Tujuan penelitian ini yaitu 1) mengembangkan mobile AR berbasis Android untuk mendukung proses pembelajaran, 2) mengimplementasikan dan menguji kelayakan aplikasi ini, dan 3) menumbuhkan motivasi peserta didik agar lebih rajin belajar terutama ilmu perhitungan dengan menggunakan mobile learning berbasis Android. Penelitian ini mengembangkan model ADDIE yang terdiri dari 5 fase keseluruhan, yaitu analisis, desain, pengembangan, penerapan, dan evaluasi. …”
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Biological characteristics, immune infiltration and drug prediction of PANoptosis related genes and possible regulatory mechanisms in inflammatory bowel disease by Minglin Zhang, Tong Liu, Lijun Luo, Yuxin Xie, Fen Wang

“…The enrichment analysis suggested that these genes were related to TNF signalling, NF-κB, pyroptosis and necroptosis. Machine learning identified three model genes: OGT, GZMB and CASP5. …”
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A Multi-Branch Convolution and Dynamic Weighting Method for Bearing Fault Diagnosis Based on Acoustic–Vibration Information Fusion by Xianming Sun, Yuhang Yang, Changzheng Chen, Miao Tian, Shengnan Du, Zhengqi Wang

“…Furthermore, its superiority across different data scales, especially in small-sample learning and stability, highlights its strong generalization capability.…”
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Unpacking the Mood States of Children and Youth in Saskatchewan, Canada, in the Context of the COVID-19 Pandemic: Insights from the “See Us, Hear Us 2.0” Study by Nahin Shakurun, Tamara Hinz, Daniel A. Adeyinka, Nazeem Muhajarine

“…Factors such as older children, hybrid learning, disrupted activities, and increased screen time worsened moods. …”
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Surgical Challenges in Multi-Vessel Minimally Invasive Coronary Artery Bypass Grafting by Jia-Ji Liu, Qing-Yu Kong, Bin You, Lin Liang, Wei Xiao, Xiao-long Ma, Feng Pan, Li-Qun Chi

“…There is a substantial learning curve associated with performing off-pump MICS CABG to treat multi-vessel disease. …”
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Enhancing pediatric congenital heart disease detection using customized 1D CNN algorithm and phonocardiogram signals by Ihtisham Ul Haq, Ghassan Husnain, Yazeed Yasin Ghadi, Nisreen Innab, Masoud Alajmi, Hanan Aljuaid

“…The research highlights the promise of combining modern signal processing with deep learning for efficient CHD screening. The suggested model exhibits outstanding performance yet, issues like dataset variability and noise persist. …”
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Detecting tropical freshly-opened swidden fields using a combined algorithm of continuous change detection and support vector machine by Ningsang Jiang, Peng Li, Zhiming Feng

“…The integration CCDC with SVM represents a novelty in combining time series analysis and machine learning techniques and helps monitor annual swidden agriculture in the tropics.…”
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Gender differences in performance under different evaluation schemes and the leaky pipeline in economics by Fabiana Rocha, Paula Pereda, Maria Dolores Montoya Diaz, Bruna Borges, Gabriel Facundes Monteiro, Luiza Karpavicius, Liz Matsunaga, Clara Brenck

“…Since the students taking the ANPEC exam were exposed to the same higher education program, after controlling for observable characteristics, we can relate the differences in performance to the exam itself rather than to differences in learning abilities. While we cannot identify the source of the performance gap, as the ANPEC exam and undergraduate grading system vary in terms of stakes, grading scheme, risk, and competitiveness (all of which can potentially affect women and men differently), we argue that our evidence suggests the need to reconsider admission exam designs to address the leaky pipeline in economics. …”
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CODE-ACCORD: A Corpus of building regulatory data for rule generation towards automatic compliance checking by Hansi Hettiarachchi, Amna Dridi, Mohamed Medhat Gaber, Pouyan Parsafard, Nicoleta Bocaneala, Katja Breitenfelder, Gonçal Costa, Maria Hedblom, Mihaela Juganaru-Mathieu, Thamer Mecharnia, Sumee Park, He Tan, Abdel-Rahman H. Tawil, Edlira Vakaj

“…Converting textual rules into machine-readable formats is challenging due to the complexities of natural language and the scarcity of resources for advanced Machine Learning (ML). Addressing these challenges, we introduce CODE-ACCORD, a dataset of 862 sentences from the building regulations of England and Finland. …”
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An automated adaptive trading system for enhanced performance of emerging market portfolios by Cristiana Tudor, Robert Sova

“…The system incorporates an Autoregressive Moving Average-Generalized AutoRegressive Conditional Heteroskedasticity model that offers an interpretability advantage over machine-learning methods. The main strength of the AATS is its ability to allow the embedded hybrid forecasting model to adapt to the changing environments that characterize EMs. …”
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Electroacupuncture Increases the Hippocampal Synaptic Transmission Efficiency and Long-Term Plasticity to Improve Vascular Cognitive Impairment by Yaling Dai, Yuhao Zhang, Minguang Yang, Huawei Lin, Yulu Liu, Wenshan Xu, Yanyi Ding, Jing Tao, Weilin Liu

“…EA at GV20 and GV24 acupoints increased the basic synaptic transmission efficiency and synaptic plasticity of the hippocampal CA3–CA1 circuit, thereby improving learning and memory ability in rats with VCI.…”
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Factors Influencing the Practice of Breast Self-Examination among Female Tertiary Students in Ho, Ghana by Rosemary Ami Amegbedzi, Joyce Komesuor, Hubert Amu, Elvis Enowbeyang Tarkang

“…Therefore, it is recommended that the Ministry of Health, the Ghana Health Service, and other stakeholders in Ghana’s healthcare should develop and implement innovative approaches and policies such as peer and support groups’ learning, and mass media BSE awareness aimed at ensuring better understanding and access to BSE education. …”
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Blood from septic patients with necrotising soft tissue infection treated with hyperbaric oxygen reveal different gene expression patterns compared to standard treatment by Julie Vinkel, Alfonso Buil, Ole Hyldegaard

“…Gene expression profiles were analysed using machine learning techniques to identify sepsis endotypes, treatment response endotypes and clinically relevant transcriptomic signatures of response to treatment. …”
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Integrative single-cell and multi-omics analyses reveal ferroptosis-associated gene expression and immune microenvironment heterogeneity in gastric cancer by Shupeng Zhang, Zhaojin Li, Gang Hu, Hekai Chen

“…In the gene selection and model validation section, critical genes were identified using machine learning algorithms, constructing a model with high predictive accuracy. …”
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The capacity of Islamic senior high school students to comprehend mathematical ideas and solve matrix problems by Ucik Fitri Handayani, Lailatul Anggraini

“…Meanwhile, the lowest percentage of students' concept comprehension indicators is applying mathematical procedures or operations in solving problems. Teachers in the learning process are advised not only to emphasize memorization but also to understand students' concepts.…”
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