Early prediction of bone destruction in rheumatoid arthritis through machine learning analysis of plasma metabolites by Zihan Wang, Tianyi Lan, Yi Jiao, Xing Wang, Hongwei Yu, Qishun Geng, Jiahe Xu, Cheng Xiao, Qingwen Tao, Yuan Xu

“…Of the 774 detected metabolites, 77 differed between patients with different outcomes. …”
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Developing an efficient explainable artificial intelligence approach for accurate reverse osmosis desalination plant performance prediction: application of SHAP analysis by Meysam Alizamir, Mo Wang, Rana Muhammad Adnan Ikram, Sungwon Kim, Kaywan Othman Ahmed, Salim Heddam

“…The modelling outcomes obtained during the evaluation stage demonstrated the efficacy of the SVR algorithm in enhancing the precision of permeate flow forecasts, utilizing relevant input variables.…”
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An explorative study on movement detection using wearable sensors in acute care hospital patients by Joris Kirchberger, Dominik Kunz, Guido Perrot, Sven Hirsch, Maren Leifke, Bianca Hölz, Lukas Geissmann, Miro Käch, Samuel Wehrli, Jens Eckstein

“…We collected raw accelerometer and gyroscope data from three different body locations (wrist, ankle, and thigh) from 40 patients at the University Hospital Basel. …”
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Method of Entry Layout under Synergistic Effects of Abutment Stress and Dynamic Stress by Wenlong Shen, Guocang Shi, Meng Wang, Tenglong Rong, Yungang Wang, Ruifeng Zhang, Xiangyu Wang, Jianbiao Bai

“…The analysis procedure can be repeatable and necessary since the rock and coal materials may be different in geological and engineering conditions.…”
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Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis by Gabriela Riemekasten, Felix Nensa, Hanna Grasshoff, René Hosch, Malte Maria Sieren, Lennart Berkel, Jörg Barkhausen, Roman Kloeckner, Franz Wegner

“…An artificial intelligence-based 3D body composition analysis (BCA) algorithm assessed muscle volume, different adipose tissue compartments, and bone mineral density. …”
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Biomechanical simulations of intracerebral hemorrhage expansion show tissue displacement has significant impact on electrical impedance tomography results by Antti Paldanius, Jussi Toivanen, Nina Forss, Daniel Strbian, Ville Kolehmainen, Jari Hyttinen

“…In-silico models are usually used for development and evaluation of algorithms for EIT image reconstruction. …”
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STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG by Raquel Fernández-Martín, Alfonso Gijón, Odile Feys, Elodie Juvené, Alec Aeby, Charline Urbain, Xavier De Tiège, Vincent Wens

“…This proof-of-concept study represents a first step towards the use of STIED and DL algorithms in the routine clinical MEG evaluation of epilepsy.…”
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Land Use/Land Cover Change Impact on Hydrological Process in the Upper Baro Basin, Ethiopia by Tewodros Getu Engida, Tewodros Assefa Nigussie, Abreham Berta Aneseyee, John Barnabas

“…Overall, LU/LC significantly affected the hydrological condition of the watershed. Therefore, different conservation strategies to maintain the stability and resilience of the ecosystem are vital.…”
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Combined detection of inflammatory proteins is beneficial for diagnosing the papillary thyroid carcinoma and nodular goiter by Yongqin Pan, Mingxi Xu, Tsz Hong Chong, Siping Xie, Kunsong Huang, Guanghao Wang, Yuhua Ma, Jinyi Li, Wah Yang

“…Receiver operating characteristic curve analysis was used to evaluate the diagnostic potential of differential expression of proteins via the area under the curve (AUC) analysis. …”
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An echo state network based on enhanced intersecting cortical model for discrete chaotic system prediction by Xubin Wang, Pei Ma, Jing Lian, Jizhao Liu, Yide Ma

“…The performance of the ESN-EICM was compared to that of a standard ESN and a Long Short-Term Memory (LSTM) network. The evaluation used data from three discrete chaotic systems (Logistic, Sine, and Ricker) for both one-step and multi-step prediction tasks.ResultsThe experimental results indicate that the ESN-EICM produced lower error metrics (MSE, RMSE, MAE) compared to the standard ESN and LSTM models across the tested systems, with the performance difference being more pronounced in multi-step forecasting scenarios. …”
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Expression‐based machine learning models for predicting plant tissue identity by Sourabh Palande, Jeremy Arsenault, Patricia Basurto‐Lozada, Andrew Bleich, Brianna N. I. Brown, Sophia F. Buysse, Noelle A. Connors, Sikta Das Adhikari, Kara C. Dobson, Francisco Xavier Guerra‐Castillo, Maria F. Guerrero‐Carrillo, Sophia Harlow, Héctor Herrera‐Orozco, Asia T. Hightower, Paulo Izquierdo, MacKenzie Jacobs, Nicholas A. Johnson, Wendy Leuenberger, Alessandro Lopez‐Hernandez, Alicia Luckie‐Duque, Camila Martínez‐Avila, Eddy J. Mendoza‐Galindo, David Cruz Plancarte, Jenny M. Schuster, Harry Shomer, Sidney C. Sitar, Anne K. Steensma, Joanne Elise Thomson, Damián Villaseñor‐Amador, Robin Waterman, Brandon M. Webster, Madison Whyte, Sofía Zorilla‐Azcué, Beronda L. Montgomery, Aman Y. Husbands, Arjun Krishnan, Sarah Percival, Elizabeth Munch, Robert VanBuren, Daniel H. Chitwood, Alejandra Rougon‐Cardoso

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Investigation of deep learning image fusion techniques for medical imaging by Angayarkanni Veeraputhiran, Muthukumar Balamurugan, Varun P. Gopi

“…Experiments on the fusion of MRI and PET medical images are being conducted to evaluate performance, algorithm stability, and other parameters. …”
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Deep learning-based analysis of 12-lead electrocardiograms in school-age children: a proof of concept study by Shuhei Toba, Yoshihide Mitani, Yusuke Sugitani, Yusuke Sugitani, Hiroyuki Ohashi, Hirofumi Sawada, Mami Takeoka, Naoki Tsuboya, Kazunobu Ohya, Noriko Yodoya, Takato Yamasaki, Yuki Nakayama, Hisato Ito, Masahiro Hirayama, Motoshi Takao

“…The specificity of the deep learning-based model for detecting abnormal electrocardiograms was not significantly different from that of the conventional algorithm. …”
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L2D2: A Novel LSTM Model for Multi-Class Intrusion Detection Systems in the Era of IoMT by Gokhan Akar, Shaaban Sahmoud, Mustafa Onat, Unal Cavusoglu, Emmanuel Malondo

“…In this paper, we propose a novel approach for detecting various intrusion attacks targeting Internet of Medical Things (IoMT) devices, utilizing an enhanced version of the LSTM deep learning algorithm. To evaluate and compare the proposed algorithm with other methods, we used the CICIoMT2024 dataset, which encompasses various types of equipment and corresponding attacks. …”
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Speaker Recognition Using Wavelet Cepstral Coefficient, I-Vector, and Cosine Distance Scoring and Its Application for Forensics by Lei Lei, She Kun

“…Moreover, linear discriminant analysis (LDA) and the within-class covariance normalization (WCNN) are added to the CDS algorithm to deal with the channel variability problem. …”
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Contrastive Learning‑based Simplified Graph Convolutional Network Recommendation by YU Yuchen, WU Siqi, ZHAO Qinghua, WU Xuhong, WANG Lei

“…The algorithm was evaluated on Amazon-Book, Yelp2018, and Gowalla datasets. …”
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Heisenberg Group-Based Digital Signatures for Secure Communications by Najla Althuniyan, Ahmed Alamer, Awais Yousaf, Muhammad Waseem, Sarah Aljohani

“…This paper proposes a new digital signature algorithm that employs the Heisenberg group over a prime field and exploits its structure to provide strong cryptographic properties. …”
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Multiple UAV Swarms Collaborative Firefighting Strategy Considering Forest Fire Spread and Resource Constraints by Pei Zhu, Rui Song, Jiangao Zhang, Ziheng Xu, Yaqi Gou, Zhi Sun, Quan Shao

“…The critical water flow rate required for fire suppression is calculated to evaluate the firefight performance, and an emergency bidding algorithm is applied to enable multiple UAV swarms collaborative firefighting under limited resources, including different payloads per UAV and swarm number. …”
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Integrating Multiple RIS for Enhanced SWIPT-IoT Performance: Optimization Strategies by Neha Sharma, Sumit Gautam, Symeon Chatzinotas, Bjorn Ottersten

“…Numerical simulations are conducted to evaluate system performance highlight rate-energy trade-off across different scenarios, considering factors such as RIS angular placement, surfaces count, element count, separation distance, EH and data rate demands. …”
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A Spatiotemporal Fusion Network for Remote Sensing Based on Global Context Attention Mechanism by Weisheng Li, Yusha Liu, Yidong Peng, Fengyan Wu

“…This network comprises an extracting feature network and a difference network. In the difference network, we introduce a GC attention mechanism that focuses on crucial details across various features, assuming different roles in different modules. …”
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