Remote Rehabilitation and Virtual Reality Interventions Using Motion Sensors for Chronic Low Back Pain: A Systematic Review of Biomechanical, Pain, Quality of Life, and Adherence O... by Marina Garofano, Rosaria Del Sorbo, Mariaconsiglia Calabrese, Massimo Giordano, Maria Pia Di Palo, Marianna Bartolomeo, Chiara Maria Ragusa, Gaetano Ungaro, Gianluca Fimiani, Federica Di Spirito, Massimo Amato, Michele Ciccarelli, Claudio Pascarelli, Giuseppe Scanniello, Placido Bramanti, Alessia Bramanti

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Machine learning-based viewers’ preference prediction on social awareness advertisements using EEG by Farhan Ishtiaque, Mohammad Tohidul Islam Miya, Fazla Rabbi Mashrur, Khandoker Mahmudur Rahman, Ravi Vaidyanathan, Syed Ferhat Anwar, Farhana Sarker, Noor Azman Ali, Huam Hon Tat, Khondaker A. Mamun, Khondaker A. Mamun

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Power Line Aerial Image Restoration Under Adverse Weather: Datasets and Baselines by Sai Yang, Bin Hu, Bojun Zhou, Fan Liu, Xiaoxin Wu, Xinsong Zhang, Juping Gu, Jun Zhou

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Visual tracking of a moving target in 360-degree virtual reality: Analysis of the effects on attention and mood by T. Sellner, P. Ehmann, J. Spielmann, F. Gogolla, A. Rösgen, J. Mayer, M. A. Schoenfeld, M. A. Schoenfeld, H. Flor

“…A pursuit training was developed for the Helix-Arena. In this study, we evaluate the effectiveness of the pursuit training in the Helix-Arena compared to a control group [CG, training on a personal computer (PC)] in 34 healthy participants. …”
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A systematic review of neural network applications for groundwater level prediction by Samuel K. Afful, Cyril D. Boateng, Emmanuel Ahene, Jeffrey N. A. Aryee, David D. Wemegah, Solomon S. R. Gidigasu, Akyana Britwum, Marian A. Osei, Jesse Gilbert, Haoulata Touré, Vera Mensah

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Liquid Biopsy Based Bladder Cancer Diagnostic by Machine Learning by Ērika Bitiņa-Barlote, Dmitrijs Bļizņuks, Sanda Siliņa, Mihails Šatcs, Egils Vjaters, Vilnis Lietuvietis, Miki Nakazawa-Miklaševiča, Juris Plonis, Edvīns Miklaševičs, Zanda Daneberga, Jānis Gardovskis

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Local Sub-Block Contrast and Spatial–Spectral Gradient Feature Fusion for Hyperspectral Anomaly Detection by Dong Zhao, Xingchen Xu, Mingtao You, Pattathal V. Arun, Zhe Zhao, Jiahong Ren, Li Wu, Huixin Zhou

“…Experimental validation based on four real-world datasets demonstrates that the proposed method outperforms seven state-of-the-art techniques, showing superior performance in both qualitative and quantitative evaluations.…”
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An empirical investigation into enhancing natural convection heat transfer through corona wind in a needle-to-cylinder configuration by Chakrit Suvanjumrat, Jetsadaporn Priyadumkol, Kunthakorn Khaothong, Weerachai Chaiworapuek

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Fusion-driven semi-supervised learning-based lung nodules classification with dual-discriminator and dual-generator generative adversarial network by Ahmed Saihood, Wijdan Rashid Abdulhussien, Laith Alzubaid, Mohamed Manoufali, Yuantong Gu

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Predicting PTSD development with early post-trauma assessments: a proof-of-concept for a concise tree-based classification method by Chia-Hao Shih, Elyssa Charlotte Feuer, Ben Kurzion, Kevin Xu, Hong Xie, Stephen R. Grider, Xin Wang

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Can clinical audits be enhanced by pathway simulation and machine learning? An example from the acute stroke pathway by Andrew Salmon, Thomas Monks, Michael Allen, Kerry Pearn, Benjamin D Bray, Richard Everson, Martin James, Ken Stein

“…Objective To evaluate the application of clinical pathway simulation in machine learning, using clinical audit data, in order to identify key drivers for improving use and speed of thrombolysis at individual hospitals.Design Computer simulation modelling and machine learning.Setting Seven acute stroke units.Participants Anonymised clinical audit data for 7864 patients.Results Three factors were pivotal in governing thrombolysis use: (1) the proportion of patients with a known stroke onset time (range 44%–73%), (2) pathway speed (for patients arriving within 4 hours of onset: per-hospital median arrival-to-scan ranged from 11 to 56 min; median scan-to-thrombolysis ranged from 21 to 44 min) and (3) predisposition to use thrombolysis (thrombolysis use ranged from 31% to 52% for patients with stroke scanned with 30 min left to administer thrombolysis). …”
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Predicting neoadjuvant chemotherapy response in locally advanced gastric cancer using a machine learning model combining radiomics and clinical biomarkers by Tong Ling, Zhichao Zuo, Liucheng Wu, Jie Ma, Tingan Wang, Mingwei Huang

“…Pre-treatment portal venous-phase computed tomography scans were used to extract 1130 radiomic features via the OnekeyAI platform software. …”
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Securing Electrical Drive Systems Against Man-in-the-Middle Attacks Using S-Box Optimized AES Encryption by J. Dheeba, Vansh Oberoi, R. Raja Singh, V. Gautam Karthik

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FloodGNN-GRU: a spatio-temporal graph neural network for flood prediction by Arnold Kazadi, James Doss-Gollin, Antonia Sebastian, Arlei Silva

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A robust and accurate feature matching method for multi-modal geographic images spatial registration by Kai Ren, Weiwei Sun, Xiangchao Meng, Gang Yang, Jiangtao Peng, Binjie Chen, Jiancheng Li

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GeNetFormer: Transformer-Based Framework for Gene Expression Prediction in Breast Cancer by Oumeima Thaalbi, Moulay A. Akhloufi

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Plasma exosomal miRNA expression and gut microbiota dysbiosis are associated with cognitive impairment in Alzheimer’s disease by Kaihao Lin, Wenxia Lin, Zhikai Guo, Cuihong Chen, Liang Chen, Xianbin Cai

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A Bioimpedance-Based Device to Assess the Volume Conduction Properties of the Tongue in Neurological Disorders Affecting Bulbar function by Xuesong Luo, Hilda V. Gutierrez Pulido, Seward Rutkove, Benjamin Sanchez

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MEF-AlloSite: an accurate and robust Multimodel Ensemble Feature selection for the Allosteric Site identification model by Sadettin Y. Ugurlu, David McDonald, Shan He

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A Multi-Goal Particle Swarm Optimizer for Test Case Prioritization by Muhammad Nazir, Arif Mehmood, Waqar Aslam, Yongwan Park, Gyu Sang Choi, Imran Ashraf

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