Investigating Similarities Across Decentralized Finance (DeFi) Services by Junliang Luo, Stefan Kitzler, Pietro Saggese

“… We explore the adoption of graph representation learning (GRL) algorithms to investigate similarities across services offered by Decentralized Finance (DeFi) protocols. …”
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Parametric optimization of the slot waveguide characteristics using a machine-learning approach by Yadvendra Singh, Suraj Jena, Harish Subbaraman

“…This specific property of the slot waveguide provides interaction between active material and electric field, which led to many interesting applications, such as optical amplification, optical switching, and optical detection in integrated photonics. In the present work, we combine machine learning (ML) algorithms and finite element simulation to predict the power confinement ( $$\hbox {P}_{conf}$$ ) and mode effective index ( $$\hbox {n}_{eff}$$ ) of slot waveguides with respect to geometric parameters such as gap, slab width, and slab height. …”
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A comprehensive survey of cyberattacks on EVs: Research domains, attacks, defensive mechanisms, and verification methods by Tawfiq Aljohani, Abdulaziz Almutairi

“…The third taxonomy discusses the countermeasures and defensive mechanisms to secure the EVs against cyberattacks, including preventive measures, detection algorithms, response strategy, and recovery techniques. …”
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A Systematic Literature Review on the Application of Machine Learning for Predicting Stunting Prevalence in Indonesia (2020–2024) by Emilda Indrisari, Hidayat Febiansyah, Bambang Adiwinoto

“…The analysis focused on the algorithms used, data types, model performance, and implementation challenges. …”
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Study of methods for extracting contours of objects on raster images of amber samples by Yu.O. Podchashynskyi, A.V. Ryzhuk

“…Effective methods and algorithms for detecting objects and their contours on raster images significantly improve the performance of TVS in applied tasks. …”
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Multi-INTACT: integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits by Jeffrey Okamoto, Xianyong Yin, Brady Ryan, Joshua Chiou, Francesca Luca, Roger Pique-Regi, Hae Kyung Im, Jean Morrison, Charles Burant, Eric B. Fauman, Markku Laakso, Michael Boehnke, Xiaoquan Wen

“…Abstract We present multi-integration of transcriptome-wide association studies and colocalization (Multi-INTACT), an algorithm that models multiple “gene products” (e.g., encoded RNA transcript and protein levels) to implicate causal genes and relevant gene products. …”
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The diagnostic and prognostic value of C1orf174 in colorectal cancer by Elham Nazari, Ghazaleh Khalili-Tanha, Ghazaleh Pourali, Fatemeh Khojasteh-Leylakoohi, Hanieh Azari, Mohammad Dashtiahangar, Hamid Fiuji, Zahra Yousefli, Alireza Asadnia, Mina Maftooh, Hamed Akbarzade, Mohammadreza Nassiri, Seyed Mahdi Hassanian, Gordon A Ferns, Godefridus J Peters, Elisa Giovannetti, Jyotsna Batra, Majid Khazaei, Amir Avan

“…Conclusion: Machine learning algorithms can be used to Identify key dysregulated genes/miRNAs involved in the pathogenesis of diseases, leading to the detection of patients in earlier stages. …”
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A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression by Hilario Gómez-Moreno, Pedro Gil-Jiménez, Sergio Lafuente-Arroyo, Roberto López-Sastre, Saturnino Maldonado-Bascón

“…A modified median filter based on a previous noise detection stage and a regression-based filter are presented and compared to other well-known state-of-the-art noise reduction algorithms. …”
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The Clinical Significance of Abnormal Electroencephalography (EEG) Patterns in Patients with Neuropsychiatric Disorders Due to Anti-NMDA Receptor Encephalitis: A Comparative Study by Alvaro Moreno-Avellán, Arely Juarez-Jaramillo, Maria del Carmen Fernandez Gonzalez-Aragon, Gerardo Quiñones-Pesqueira, Luz Maria Pineda-Centeno, Mariana Espinola-Nadurille, Victoria Martinez-Angeles, Francisco Martinez-Carrillo, Veronica Rivas-Alonso, Daniel San-Juan, Jose Flores-Rivera, Jesus Ramirez-Bermudez

“…These findings support the integration of EEG into diagnostic algorithms to guide early detection and management of autoimmune encephalitis.…”
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Opportunistic Diagnostics of Dental Implants in Routine Clinical Photon-Counting CT Acquisitions by Maurice Ruetters, Holger Gehrig, Christian Mertens, Sinan Sen, Ti-Sun Kim, Heinz-Peter Schlemmer, Christian H. Ziener, Stefan Schoenberg, Matthias Froelich, Marc Kachelrieß, Stefan Sawall

“…PCCT offers excellent image quality for peri-implant assessments and enables incidental detection of dental pathologies without additional radiation exposure. …”
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ML‐UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper by Warren G. Hill, Bryce MacIver, Gary A. Churchill, Mariana G. DeOliveira, Mark L. Zeidel, Marcelo Cicconet

“…We have developed a machine learning algorithm based on Region‐based Convolutional Neural Networks (Mask‐RCNN) that was trained in object recognition to detect and quantitate urine spots across a broad range of sizes—ML‐UrineQuant. …”
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Energy Efficiency in Measurement and Image Reconstruction Processes in Electrical Impedance Tomography by Barbara Stefaniak, Tomasz Rymarczyk, Dariusz Wójcik, Marta Cholewa-Wiktor, Tomasz Cieplak, Zbigniew Orzeł, Janusz Gudowski, Ewa Golec, Michał Oleszek, Marcin Kowalski

“…This paper presents an energy optimization approach to applying electrical impedance tomography (EIT) for medical diagnostics, particularly in detecting lung diseases. The designed Lung Electrical Tomography System (LETS) incorporates 102 electrodes and advanced image reconstruction algorithms. …”
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Prediction of Parkinson Disease Using Long-Term, Short-Term Acoustic Features Based on Machine Learning by Mehdi Rashidi, Serena Arima, Andrea Claudio Stetco, Chiara Coppola, Debora Musarò, Marco Greco, Marina Damato, Filomena My, Angela Lupo, Marta Lorenzo, Antonio Danieli, Giuseppe Maruccio, Alberto Argentiero, Andrea Buccoliero, Marcello Dorian Donzella, Michele Maffia

“…Notably, by combining a comprehensive set of long-term, short-term, and non-standard acoustic features, unlike previous studies that typically focused on only a subset, our study achieved higher predictive performance, offering a more robust model for early PD detection. <b>Conclusions:</b> This study highlights the potential of combining advanced acoustic analysis with ML algorithms to develop non-invasive and reliable tools for early PD detection, offering substantial benefits for the healthcare sector.…”
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Automated Global Classification of Surface Layer Stratification Using High‐Resolution Sea Surface Roughness Measurements by Satellite Synthetic Aperture Radar by Justin E. Stopa, Chen Wang, Doug Vandemark, Ralph Foster, Alexis Mouche, Bertrand Chapron

“…An automated machine learning algorithm identifies the coherent structures impressed on the images. …”
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Mathematical Modelling of Glucose-Insulin System and Test of Abnormalities of Type 2 Diabetic Patients by Wellars Banzi, Immaculate Kambutse, Vincent Dusabejambo, Eric Rutaganda, Froduald Minani, Japhet Niyobuhungiro, Lydie Mpinganzima, Jean Marie Ntaganda

“…In order to identify and evaluate possible abnormalities of type 2 diabetic patients, the Sampling Importance Resampling (SIR) particle filtering algorithm is used and implemented through discretization of the developed mathematical model. …”
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Advances in Data Pre-Processing Methods for Distributed Fiber Optic Strain Sensing by Bertram Richter, Lisa Ulbrich, Max Herbers, Steffen Marx

“…Dedicated algorithms should be used to detect and remove SRAs. …”
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Artificial Intelligence in Diagnosis of Heart Failure by Yuji Xie, Linyue Zhang, Wei Sun, Ye Zhu, Zisang Zhang, Leichong Chen, Mingxing Xie, Li Zhang

“…Artificial intelligence (AI) algorithms have the potential to transform HF care by enhancing clinical decision‐making processes, enabling the early detection of patients at risk for subclinical or worsening HF. …”
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The Use of Selected Machine Learning Methods in Dairy Cattle Farming: A Review by Wilhelm Grzesiak, Daniel Zaborski, Marcin Pluciński, Magdalena Jędrzejczak-Silicka, Renata Pilarczyk, Piotr Sablik

“…The aim of this review was to present selected machine learning (ML) algorithms used in dairy cattle farming in recent years (2020–2024). …”
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Domain Adaptation in Application to Gravitational Lens Finding by Hanna Parul, Sergei Gleyzer, Pranath Reddy, Michael W. Toomey

“…To discover these rare objects, efficient automated detection methods need to be developed. In this work, we assess the performance of three domain adaptation (DA) techniques—adversarial discriminative DA, Wasserstein distance guided representation learning (WDGRL), and supervised domain adaptation (SDA)—in enhancing lens-finding algorithms trained on simulated data when applied to observations from the Hyper Suprime-Cam Subaru Strategic Program. …”
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Uncertainty analysis based on Bayesian inference for partial defect verification of PWR spent nuclear fuel by Hojik Kim, Hyung-Joo Choi, Woojin Kim, Seungmin Lee, Chul Hee Min, Sung-Woo Kwak

“…Unlike traditional SNF defect detection algorithms that estimate specific values, the proposed method estimates distributions, thus providing belief in the estimates. …”
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