Use of machine learning to predict creativity among nurses: a multidisciplinary approach by Rola H. Mudallal, Majd T. Mrayyan, Mohammad Kharabsheh

“…Methods A multidisciplinary design comprising machine learning algorithms mixed with a descriptive, cross-sectional, correlational design was implemented to enhance data analysis and decision-making. …”
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Dynamic Response Prediction of Railway Bridges Considering Train Load Duration Using the Deep LSTM Network by Sui Tan, Xiandong Ke, Zhenhao Pang, Jianxiao Mao

“…Therefore, this study develops a novel framework, combining the train–bridge coupling mechanism and deep learning algorithms to efficiently predict the train-induced bridge responses while considering train load duration. …”
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Best practices and joint calling of the HumanExome BeadChip: the CHARGE Consortium. by Megan L Grove, Bing Yu, Barbara J Cochran, Talin Haritunians, Joshua C Bis, Kent D Taylor, Mark Hansen, Ingrid B Borecki, L Adrienne Cupples, Myriam Fornage, Vilmundur Gudnason, Tamara B Harris, Sekar Kathiresan, Robert Kraaij, Lenore J Launer, Daniel Levy, Yongmei Liu, Thomas Mosley, Gina M Peloso, Bruce M Psaty, Stephen S Rich, Fernando Rivadeneira, David S Siscovick, Albert V Smith, Andre Uitterlinden, Cornelia M van Duijn, James G Wilson, Christopher J O'Donnell, Jerome I Rotter, Eric Boerwinkle

“…., minor allele frequency [MAF] <0.01) is the difficulty that automated clustering algorithms have to accurately detect and assign genotype calls. …”
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Identification of developmental and reproductive toxicity of biocides in consumer products using ToxCast bioassays data and machine learning models by Donghyeon Kim, Siyeol Ahn, Jinhee Choi

“…Based on the assumption that chemicals active in these ToxCast assays and their machine learning models may have DART potential, we prioritized active biocides in consumer products. …”
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Analysis of multiple faults in induction motor using machine learning techniques by Puja Pohakar, Ravi Gandhi, Surender Hans, Gulshan Sharma, Pitshou N. Bokoro

“…Due to their limits, machine learning algorithms outperform traditional methods in real-time fault diagnosis, predictive maintenance, and multi-fault categorization. …”
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Predicting adolescent psychopathology from early life factors: A machine learning tutorial by Faizaan Siddique, Brian K. Lee

“…The best performing algorithms were elastic net and gradient boosted trees. …”
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Bioinformatic Methodologies in Assessing Gut Microbiota by James Douglas Fox, Austin Sims, Morgan Ross, Jeffery Bettag, Alexandra Wilder, Dylan Natrop, Alison Borsotti, Sree Kolli, Shaurya Mehta, Hema Verma, Kento Kurashima, Chandrashekhara Manithody, Arun Verma, Ajay Jain

“…Bioinformatics tools and algorithms process these data to identify microbial taxa and quantify and elucidate their roles within the microbiome. …”
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Development and multicenter validation of an AI driven model for quantitative meibomian gland evaluation by Li Li, Kunhong Xiao, Taichen Lai, Kunfeng Lai, Jiawen Lin, Zongyuan Ge, Lingyi Liang, Hao Huang, Xiaoshan Zhang, Li Liu, Yujie Wang, Xianwen Shang, Mingguang He, Ying Xue, Zhuoting Zhu

“…This AI tool offers a standardized, efficient, and objective method for meibography image analysis, which may improve diagnostic precision and assist in the clinical management of meibomian gland dysfunction across diverse populations.…”
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Using Artificial Intelligence to Enhance Myelodysplastic Syndrome Diagnosis, Prognosis, and Treatment by Fabio Stagno, Giuseppe Mirabile, Patricia Rizzotti, Adele Bottaro, Antonio Pagana, Sebastiano Gangemi, Alessandro Allegra

“…Artificial intelligence (AI) can improve risk assessment and diagnosis, as well as boost the precision of clinical outcome prediction and illness classification. Algorithms based on artificial intelligence may be potentially helpful in discovering new needs for myelodysplastic syndrome-affected patients, choosing treatment and assessing minimal residual disease. …”
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Rapid and accurate multi-phenotype imputation for millions of individuals by Lin-Lin Gu, Hong-Shan Wu, Tian-Yi Liu, Yong-Jie Zhang, Jing-Cheng He, Xiao-Lei Liu, Zhi-Yong Wang, Guo-Bo Chen, Dan Jiang, Ming Fang

“…In the present study, we have developed a multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms. We demonstrate by extensive simulations that PIXANT is reliable, robust and highly resource-efficient. …”
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Unsupervised Clustering of Cell Populations in Germinal Centers Using Multiplexed Immunofluorescence by Simon Burgermeister, Michail Orfanakis, Spiros Georgakis, Cloe Brenna, Helen Lindsay, Craig Fenwick, Giuseppe Pantaleo, Raphael Gottardo, Constantinos Petrovas

“…We evaluate multiple clustering algorithms and find that k-means clustering provides the most effective separation of distinct cell subsets. …”
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Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?—A Systematic Review by Sergiu-Ciprian Matei, Sorin Olariu, Ana-Maria Ungureanu, Daniel Malita, Flavia Medana Petrașcu

“…This study aims to evaluate the efficacy and feasibility of AI algorithms in diagnosing venous diseases and explore their potential impact on clinical practice. …”
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Data transfers for nuclear reactor multiphysics studies using the MOOSE framework by Guillaume L. Giudicelli, Guillaume L. Giudicelli, Fande Kong, Roy Stogner, Logan Harbour, Derek Gaston, Alexander Lindsay, Zachary Prince, Lise Charlot, Stefano Terlizzi, Mahmoud Eltawila, April Novak

“…Advanced nuclear reactor cores are governed by multiple physical phenomena which should be all be resolved, and the coupling of these physics would also need to be resolved spatially in a high-fidelity approach, while lower fidelity may leverage integrated quantities for the coupling instead. …”
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Small Molecules in the Treatment of Acute Severe Ulcerative Colitis: A Review of Current Evidence by Raffaele Pellegrino, Giuseppe Imperio, Ilaria De Costanzo, Michele Izzo, Fabio Landa, Assunta Tambaro, Antonietta Gerarda Gravina, Alessandro Federico

“…Despite this approach, a significant proportion of patients fail to respond to either corticosteroids or infliximab and may require alternative therapeutic options if there is no urgent surgical necessity. …”
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A Multiscale Convolution SAR Image Target Recognition Method Based on Complex-Valued Neural Networks by Guangyu Hou, Zhihui Xin, Guisheng Liao, Penghui Huang, Yuhao Huang, Rui Zou

“…Many deep learning algorithms rely solely on amplitude information, ignoring phase information, which may result in the loss of information in the original complex-valued SAR image and suboptimal performance. …”
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Target repositioning using multi-layer networks and machine learning: The case of prostate cancer by Milan Picard, Marie-Pier Scott-Boyer, Antoine Bodein, Mickaël Leclercq, Julien Prunier, Olivier Périn, Arnaud Droit

“…However, over-reliance on PPI networks and the assumption that potential targets are necessarily near known genes can introduce biases that may limit the effectiveness of these methods. This study addresses these limitations in two ways. …”
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Review of Artifacts and Related Processing in Ophthalmic Optical Coherence Tomography Angiography (OCTA) by Zhefan Lin, Yitao Hu, Gongpu Lan, Jingjiang Xu, Jia Qin, Lin An, Yanping Huang

“…However, various imaging artifacts may be generated during OCTA data acquisition and processing, originating from a number of factors such as multiple light scattering, tissue motion, improper device operation and signal processing algorithms. …”
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A Dynamic Spike Sorter for Multiscale Nanoelectrode Array Recordings by Shivani Shukla, Callum Walsh, Shashank Bansal, Johannes Leugering, Abhinav Uppal, Vikrant Jaltare, Gert Cauwenberghs, Sreekanth H. Chalasani, Zeinab Jahed

“…Advanced sorting algorithms tailored for nanoelectrode array recordings are essential for unlocking the full potential of next generation, high throughput neuroelectronic devices and achieving a deeper understanding of neuronal dynamics.…”
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Behavior Analysis With Integrated Visual-Motor Tracking for Developmental Coordination Disorder by Ruimin Li, Hong Fu, Yang Zheng, Shuiping Gou, Jane Jie Yu, Xiaowei Kong, Hongmin Wang

“…Developmental coordination disorder (DCD) is a motor learning disability with a prevalence of 5&#x0025;-6&#x0025; in school-aged children, which may seriously affect the physical and mental health of affected children. …”
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REST Network: An Ensemble Deep Learning Approach for EV Charging Load Forecasting in Artificial Port Supply Chains by Elham Abdullah Alghamdi, Monagi Hassan Alkinani, Abdulwahab Ali Almazroi, Mohammed Alqarni, Eman Ali Aldhahri, Nasir Ayub

“…Traditional forecasting algorithms can fail to address logistics&#x2019; complicated, variable charge patterns and uneven data. …”
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