Remote sensing-based maize growth process parameters revel the maize yield: a comparison of field- and regional-scale by Minghan Cheng, Xiuliang Jin, Chenwei Nie, Kaihua Liu, Tianao Wu, Yuping Lv, Shuaibing Liu, Xun Yu, Yi Bai, Yadong Liu, Lin Meng, Xiao Jia, Yuan Liu, Lili Zhou, Fei Nan

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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

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Predicting suicidality in people living with HIV in Uganda: a machine learning approach by Anthony B. Mutema, Anthony B. Mutema, Anthony B. Mutema, Lillian Linda, Lillian Linda, Daudi Jjingo, Segun Fatumo, Segun Fatumo, Eugene Kinyanda, Allan Kalungi, Allan Kalungi, Allan Kalungi

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Construction of a risk prediction model for occupational noise-induced hearing loss using routine blood and biochemical indicators in Shenzhen, China: a predictive modelling study by Wenting Feng, Wen Zhang, Yan Guo, Naixing Zhang, Liang Zhou, Dafeng Lin, Linlin Chen, Caiping Li, Liuwei Shi, Xiangli Yang, Peimao Li, Dianpeng Wang

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Prevention of fetal brain injury in category II tracings by Masahiro Nakao, Michael G. Ross, Shoichi Magawa, Satoshi Toyokawa, Kiyotake Ichizuka, Naohiro Kanayama, Shoji Satoh, Nanako Tamiya, Akihito Nakai, Keiya Fujimori, Tsugio Maeda, Akira Oka, Hideaki Suzuki, Mitsutoshi Iwashita, Tomoaki Ikeda

“…In rapid progression cases, physicians' decisions to deliver the fetus occurred at ~BDecf 8 mEq/L, whereas the “decisions” did not occur until BDecf reached 12 mEq/L in slow progression cases. …”
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Rapid inference of antibiotic susceptibility phenotype of uropathogens using metagenomic sequencing with neighbor typing by Amanda C. Carroll, Leanne Mortimer, Hiren Ghosh, Sandra Reuter, Hajo Grundmann, Karel Brinda, William P. Hanage, Angel Li, Aimee Paterson, Andrew Purssell, Ashley Rooney, Noelle R. Yee, Bryan Coburn, Shola Able-Thomas, Martin Antonio, Allison McGeer, Derek R. MacFadden

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Evaluation criteria of centralization options in the architecture of multicomputer systems with traps and baits by Antonina Kashtalian, Sergii Lysenko, Anatoliy Sachenko, Bohdan Savenko, Oleg Savenko, Andrii Nicheporuk

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Progress and key technology analysis of bronchoscopic robot by Xingguang DUAN, Dongsheng XIE, Fengxinyun FANG, Rui HE, Changsheng LI

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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

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Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology by Yinhu Gao, Peizhen Wen, Yuan Liu, Yahuang Sun, Hui Qian, Xin Zhang, Huan Peng, Yanli Gao, Cuiyu Li, Zhangyuan Gu, Huajin Zeng, Zhijun Hong, Weijun Wang, Ronglin Yan, Zunqi Hu, Hongbing Fu

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Molecular feature-based classification of retroperitoneal liposarcoma: a prospective cohort study by Mengmeng Xiao, Xiangji Li, Fanqin Bu, Shixiang Ma, Xiaohan Yang, Jun Chen, Yu Zhao, Ferdinando Cananzi, Chenghua Luo, Li Min

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Preoperatively-determined Red Distribution Width (RDW) predicts prolonged length of stay after single-level spinal fusion in elderly patients by Anton Früh, Dietmar Frey, Adam Hilbert, Claudius Jelgersma, Christian Uhl, Nitzan Nissimov, Peter Truckenmüller, David Wasilewski, Dimitrios Rallios, Matthias Hoppe, Simon Bayerl, Nils Hecht, Peter Vajkoczy, Lars Wessels

“…Prolonged length of stay (pLOS) was defined as a length ≥ the 3rd quartile of LOS of all included patients. Classical correlation analysis, Receiver-operating characteristic (ROC) and new machine learning algorithms) were used. …”
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Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector by A. Gavrikov, V. Cerrone, A. Serafini, R. Brugnera, A. Garfagnini, M. Grassi, B. Jelmini, L. Lastrucci, S. Aiello, G. Andronico, V. Antonelli, A. Barresi, D. Basilico, M. Beretta, A. Bergnoli, M. Borghesi, A. Brigatti, R. Bruno, A. Budano, B. Caccianiga, A. Cammi, R. Caruso, D. Chiesa, C. Clementi, S. Dusini, A. Fabbri, G. Felici, F. Ferraro, M.G. Giammarchi, N. Giudice, R.M. Guizzetti, N. Guardone, C. Landini, I. Lippi, S. Loffredo, L. Loi, P. Lombardi, C. Lombardo, F. Mantovani, S.M. Mari, A. Martini, L. Miramonti, M. Montuschi, M. Nastasi, D. Orestano, F. Ortica, A. Paoloni, E. Percalli, F. Petrucci, E. Previtali, G. Ranucci, A.C. Re, M. Redchuck, B. Ricci, A. Romani, P. Saggese, G. Sava, C. Sirignano, M. Sisti, L. Stanco, E. Stanescu Farilla, V. Strati, M.D.C. Torri, A. Triossi, C. Tuvè, C. Venettacci, G. Verde, L. Votano

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Investigation of statistical methods used in prognostic prediction models for obstetric care: A 10 year‐span cross‐sectional study by Jing Tan, Chunrong Liu, Min Yang, Yiquan Xiong, Shiyao Huang, Yana Qi, Meng Chen, Lehana Thabane, Xinghui Liu, Lin He, Xin Sun

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Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe by Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
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A Novel RMS-Driven Deep Reinforcement Learning for Optimized Portfolio Management in Stock Trading by Asma Sattar, Amna Sarwar, Saira Gillani, Maryam Bukhari, Seungmin Rho, Muhammad Faseeh

“…Algorithmic stock trading has improved tremendously, with Reinforcement Learning (RL) algorithms being more adaptable than classic approaches like mean reversion and momentum. …”
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Designing and planning a bioethanol supply chain network under uncertainty using a data-driven robust optimization model under disjunctive uncertainty sets by Farzaneh MansooriMooseloo, Maghsoud Amiri, Mohammad Taghi Taghavi Fard, Mostafa Hajiaghaei-Keshteli

“…Additionally, using a three-objective model based on a sustainable development approach that simultaneously considers economic, social, and environmental components, enhances the comprehensiveness of this research, providing more realistic and detailed results.…”
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Delivering data: A real-world dataset for last-mile delivery optimizationZenodo by Anna Vrani, Savvas D. Apostolidis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos

“…The collected matrices were processed and structured for direct use in VRP algorithms.The dataset offers substantial reuse potential by serving as a benchmark for evaluating VRP algorithms, enabling the comparison of optimization methods based on real-world logistics problems. …”
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A conceptual digital twin framework for supply chain recovery and resilience by Oluwagbenga Victor Ogunsoto, Jessica Olivares-Aguila, Waguih ElMaraghy

“…This aids supply chain (SC) managers in making informed decisions. In the first phase, machine learning algorithms, including logistic regression and Long Short-Term Memory (LSTM), were trained on Kerala India's precipitation data to predict floods. …”
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Access and benefit sharing biological materials for machines: Artificial intelligence, machine learning and deep learning by Charles Lawson, Elizabeth Englezos, Michelle Rourke

“…We speculate these challenges are in three distinct scenarios: (1) data used to train the AI models; (2) data used to test (and verify) the AI models; and (3) data used in applying the models to reveal useful patterns. …”
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