Deep learning reconstruction of zero-echo time sequences to improve visualization of osseous structures and associated pathologies in MRI of cervical spine by Malwina Kaniewska, Fabio Zecca, Carina Obermüller, Falko Ensle, Eva Deininger-Czermak, Maelene Lohezic, Roman Guggenberger

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Experimental Setup and Machine Learning-Based Prediction Model for Electro-Cyclone Filter Efficiency: Filtering of Ship Particulate Matter Emission by Aleksandr Šabanovič, Jonas Matijošius, Dragan Marinković, Aleksandras Chlebnikovas, Donatas Gurauskis, Johannes H. Gutheil, Artūras Kilikevičius

“…In this paper, a random forest machine learning model developed to predict particulate concentrations post-cleaning demonstrated robust performance (MAE = 0.49 P/cm³, <i>R</i>² = 0.97). …”
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Predicting bullying victimization among adolescents using the risk and protective factor framework: a large-scale machine learning approach by Ethan Low, Joshua Monsen, Lindsay Schow, Rachel Roberts, Lucy Collins, Hayden Johnson, Carl L. Hanson, Quinn Snell, E. Shannon Tass

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Effect of a Novel Training Program in Patients With Chronic Shoulder Pain Based on Implicit Motor Learning: Pilot and Feasibility Study. by Annelies Maenhout, Wieger Heijenk, Peter Glashouwer, Lore Quatacker, Luna Praet, Dorien Borms

“…# Background Implicit motor learning has been shown to be effective for learning sports-related motor skills. …”
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Shapley additive explanation on machine learning predictions of fatigue lifetimes in piston aluminum alloys under different manufacturing and loading conditions by Mohammad Azadi, Mahmood Matin

Subjects: “…machine learning…”
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FACTORS INFLUENCING ENGLISH LEARNING MOTIVATION: A STUDY OF THE PERSPECTIVES OF NON-ENGLISH MAJORS AT A PUBLIC UNIVERSITY IN HANOI, VIETNAM by Ngoc My Trinh

Subjects: “…English learning…”
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Machine learning based QSAR and Molecular Dynamics simulations in the structural design and mechanism of action of imidazole derivatives with anti-melanoma activity by Rosalvo Ferreira de Oliveira Neto, Sérgio Ruschi Bergamachi Silva, Cintia Emi Yanaguibashi Leal, Edilson Beserra de Alencar Filho

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A robust transfer learning approach for high-dimensional linear regression to support integration of multi-source gene expression data. by Lulu Pan, Qian Gao, Kecheng Wei, Yongfu Yu, Guoyou Qin, Tong Wang

“…Transfer learning aims to integrate useful information from multi-source datasets to improve the learning performance of target data. …”
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Prediction of Ship Traffic Flow and Congestion Based on Extreme Learning Machine with Whale Optimization Algorithm and Fuzzy c-Means Clustering by Yongjun Chen, Ming Huang, Kaixuan Song, Tengfei Wang

“…We propose a method for predicting the traffic flow of ships by applying the whale optimization algorithm to an extreme learning machine. The method considers external environmental uncertainty and complexity of ships navigating in traffic-intensive waters. …”
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A PD-Type Iterative Learning Control for a Class of Switched Discrete-Time Systems with Model Uncertainties and External Noises by Xuan Yang

“…A PD-type iterative learning control algorithm is applied to a class of linear discrete-time switched systems for tracking desired trajectories. …”
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Critical Clinical forms of influenza AH1N1: What we have learned from assisting the ill in Cienfuegos. by Grupo Operativo Provincial de Atención Médica a los enfermos adultos hospitalizados

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Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: A comprehensive review of COVID-19 detection by Md Shofiqul Islam, Khondokar Fida Hasan, Hasibul Hossain Shajeeb, Humayan Kabir Rana, Md. Saifur Rahman, Md. Munirul Hasan, AKM Azad, Ibrahim Abdullah, Mohammad Ali Moni

Subjects: “…Deep learning…”
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Driving Motivation in Irish Language Learning: An analysis of variation in post-primary pupil attitudes to Irish in the Growing Up in Ireland study by Emily Barnes, Joe Condon, Ann Devitt, Noel Ó Murchadha

“… This study provides a novel perspective on minority language motivation using Situated Expectancy Value Theory to examine the attitudes of post-primary students in Ireland to learning the national minority language, Irish.  The paper uses data from Growing Up in Ireland, the national longitudinal study of the well-being and development of children and young people in Ireland, to explore factors influencing young people’s motivation in relation to learning the Irish language, controlling for overall engagement with schooling.  …”
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Integration of ground-based and remote sensing data with deep learning algorithms for mapping habitats in Natura 2000 protected oak forests by Lucia Čahojová, Ivan Jarolímek, Barbora Klímová, Michal Kollár, Michaela Michalková, Karol Mikula, Aneta A. Ožvat, Denisa Slabejová, Mária Šibíková

“…This study aims to combine ground-based and remote sensing data utilising deep learning techniques to map protected forest habitats and communities within the Natura 2000 network. …”
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Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis by Tito Bassani, Andrea Cina, Fabio Galbusera, Andrea Cazzato, Maria Elena Pellegrino, Domenico Albano, Luca Maria Sconfienza

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Application of Non-Supervised Learning Tools and Visualization Techniques to Understand the Intrinsic Freshmen Enrollment Segmentation: An application to freshmen engineering students. by Patricio Salas, Rodrigo De la Fuente, Patricio Sáez, Andrés Riquelme

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Involving migrants in the development of guidelines for communication in cross-cultural general practice consultations: a participatory learning and action research project by Chris van Weel, Anne MacFarlane, Maria van den Muijsenbergh, Tomas de Brún, Evelyn van Weel-Baumgarten, Mary O'Reilly-de Brún, Ekaterina Okonkwo, Jean Samuel Bonsenge Bokanga, Maria Manuela De Almeida Silva, Florence Ogbebor, Aga Mierzejewska, Lovina Nnadi

“…In this paper, we focus on findings about the use of formal versus informal interpreters because dialogues about these issues emerged as central to the identification of recommendations for best practice.Design This qualitative case study involved a Participatory Learning and Action (PLA) research methodology.Participants The sample comprised 80 stakeholders: 51 from migrant communities; 15 general practitioners (GPs) and general practice staff; 7 established migrants as peer researchers; 5 formal, trained interpreters; and 2 service planners from the national health authority.Setting Galway, Ireland.Results There was 100% consensus across stakeholder groups that while informal interpreters have uses for migrants and general practice staff, they are not considered acceptable as best practice. …”
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Machine learning for predicting neoadjuvant chemotherapy effectiveness using ultrasound radiomics features and routine clinical data of patients with breast cancer by Pu Zhou, Pu Zhou, Hongyan Qian, Pengfei Zhu, Jiangyuan Ben, Jiangyuan Ben, Guifang Chen, Qiuyi Chen, Lingli Chen, Jia Chen, Ying He, Ying He

“…BackgroundThis study explores the clinical value of a machine learning (ML) model based on ultrasound radiomics features of primary foci, combined with clinicopathologic factors to predict the pathological complete response (pCR) of neoadjuvant chemotherapy (NAC) for patients with breast cancer (BC).MethodWe retrospectively analyzed ultrasound images and clinical information from 231 participants with BC who received NAC. …”
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Accurate recognition of micromorphology images of epoxy coatings for deep-sea environments based on a deep learning super-resolution method by JiaQi Pan, Furou Liu, Jia Feng, Fandi Meng, Yufan Chen, Jianning Chi, Zelan Li, Jie Li, Li Liu

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PiLiMoT: A Modified Combination of LoLiMoT and PLN Learning Algorithms for Local Linear Neurofuzzy Modeling by Atiye Sarabi-Jamab, Babak N. Araabi

“…Locally linear model tree (LoLiMoT) and piecewise linear network (PLN) learning algorithms are two approaches in local linear neurofuzzy modeling. …”
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