RISK FACTORS OF ARRHYTHMIAS IN PATIENTS WITH ACUTE DECOMPENSATION OF CHRONIC HEART FAILURE by N. V. Larionova, A. M. Shutov, M. V. Menzorov, E. V. Efremova, V. V. Kasalinskaya

“…Twenty-four-hour ECG recordings were performed on 1 and 10 days of hospitalization using automatic algorithm to measure QT and heart rate for analyze the arrhythmogenic factors. …”
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Dual-Phase Severity Grading of Strawberry Angular Leaf Spot Based on Improved YOLOv11 and OpenCV by Yi-Xiao Xu, Xin-Hao Yu, Qing Yi, Qi-Yuan Zhang, Wen-Hao Su

“…Furthermore, an OpenCV-based threshold segmentation algorithm based on H-channel thresholds in the HSV color space achieved accurate lesion segmentation. …”
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FinSafeNet: securing digital transactions using optimized deep learning and multi-kernel PCA(MKPCA) with Nyström approximation by Ahmad Raza Khan, Shaik Shakeel Ahamad, Shailendra Mishra, Mohd Abdul Rahim Khan, Sunil Kumar Sharma, Abdullah AlEnizi, Osama Alfarraj, Majed Alowaidi, Manoj Kumar

“…These improvements further help the model to detect the relevant features in transaction data that may present a threat to the security of the system. …”
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Systematic Construction and Validation of a Novel Ferroptosis-Related Gene Model for Predicting Prognosis in Cervical Cancer by Wentao Qin, Can He, Daqiong Jiang, Yang Gao, Yu Chen, Min Su, Yuanjun Yang, Zhao Yang, Hongbing Cai, Hua Wang

“…Ferroptosis-related differential genes in cervical cancer were detected using the “limma” R function and WGCNA. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analysis were conducted to develop a novel prognostic signature. …”
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On-Chip Age Estimation Using Machine Learning by Turki Alnuayri, Saqib Khursheed, Daniele Rossi

“…The machine learning (ML) algorithm of support vector regression (SVR) is adapted for this application, using a training process that involves operating temperature, <inline-formula> <tex-math notation="LaTeX">$\tau _{dv}$ </tex-math></inline-formula>, f, aging time and inter-die and intra-die process variation (PV). …”
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Identification of Exosome-Associated Biomarkers in Diabetic Foot Ulcers: A Bioinformatics Analysis and Experimental Validation by Tianbo Li, Lei Gao, Jiangning Wang

“…Support vector machine–recursive feature elimination (SVM-RFE) and the Boruta random forest algorithm distilled five biomarkers (DIS3L, EXOSC7, SDC1, STX11, SYT17). …”
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Photodynamic therapy in the treatment of recurrent nasal cavity and paranasal sinus cancer by M. V. Vusik, V. I. Shtin, O. V. Cheremisina, K. Yu. Menshikov, V. A. Novikov

“…Inclusion of intraoperative PDD and PDT in the treatment algorithm for nasal cavity and paranasal sinus recurrent carcinomas signifcantly increases the disease-free and overall survival of patients.…”
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Digital Technology of Assesment the Power Capacity of Tractor Fleet of an Agricultural Enterprise by V. V. Alt, O. F. Savchenko, O. V. Elkin

“…The authors have shown a possibility of reducing costs required to maintain the detected power deviations due to excessive fuel consumption through timely repair and adjustment-and-control actions. …”
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Revolutionizing Water Quality Monitoring with Artificial Intelligence: A Systematic Review by Mahmoud Saleh Al-Khafaji, Layth Abdulameer, Muthanna M. A. AL-Shammari, Najah M. L. Al Maimuri, Anmar Dulaimi, Dhiya Al‑Jumeily

“…This systematic review addresses these gaps by evaluating the transformative role of artificial intelligence (AI) in revolutionizing monitoring practices through two novel mechanisms: (1) enhanced multivariate data fidelity via Internet of Things (IoT)-sensor networks and satellite remote sensing, and (2) predictive modeling precision using machine learning (ML) algorithms. By synthesizing 1,032 studies (2011–2025), we demonstrate that AI-driven systems achieve 94% accuracy in prediction and reduce field sampling costs by 60% through Landsat 8 satellite integration. …”
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Application of the Integral Energy Criterion and Neural Network Model for Helicopter Turboshaft Engines’ Vibration Characteristics Analysis by Serhii Vladov, Maryna Bulakh, Denys Baranovskyi, Eduard Kisiliuk, Victoria Vysotska, Maksym Romanov, Jan Czyżewski

“…It averages the assessment of unique signal processing algorithms, which ensures reliable defect classification under flight vibration conditions. …”
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Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers by Piya Prajumwongs, Attapol Titapun, Vasin Thanasukarn, Apiwat Jareanrat, Natcha Khuntikeo, Krit Rattanarak, Nisana Namwat, Poramate Klanrit, Arporn Wangwiwatsin, Jarin Chindaprasirt, Supinda Koonmee, Prakasit Sa-Ngiamwibool, Nattha Muangritdech, Sawanya Charoenlappanit, Janthima Jaresitthikunchai, Sittiruk Roytrakul, Watcharin Loilome

“…Abstract This study aimed to investigate the potential of peptide mass fingerprints (PMFs) of the serum peptidome using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), in combination with machine learning algorithms—support vector machine (SVM) and random forest (RF)—for the diagnosis and classification of hepato-pancreato-biliary (HPB) cancers. …”
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High-Quality Multispectral Image Reconstruction for the Spectral Camera Based on Ghost Imaging via Sparsity Constraints Using CoT-Unet by Tao Hu, Jianxia Chen, Shu Wang, Jianrong Wu, Ziyan Chen, Zhifu Tian, Ruipeng Ma, Di Wu

“…To solve the problem of poor quality in ghost imaging via sparsity constraints (GISC) multispectral image reconstruction with correlation operations and compressed sensing algorithms under low sampling rate detection conditions, we propose an end-to-end deep-learning-based method. …”
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New insights into biomarkers and risk stratification to predict hepatocellular cancer by Katrina Li, Brandon Mathew, Ethan Saldanha, Puja Ghosh, Adrian R. Krainer, Srinivasan Dasarathy, Hai Huang, Xiyan Xiang, Lopa Mishra

“…This review highlights the performance of these novel biomarkers and algorithms from a mechanistic perspective and provides new insight into how pathological processes can be detected through blood-based biomarkers. …”
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Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data by Haniyeh Rafiepoor, Alireza Ghorbankhanloo, Kazem Zendehdel, Zahra Zangeneh Madar, Sepideh Hajivalizadeh, Zeinab Hasani, Ali Sarmadi, Behzad Amanpour‐Gharaei, Mohammad Amin Barati, Mozafar Saadat, Seyed‐Ali Sadegh‐Zadeh, Saeid Amanpour

“…Ten classification algorithms were applied to the dataset. The accuracy, sensitivity, precision, and feature importance in the machine learning algorithms were assessed and compared to previous studies for evaluation. …”
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Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare by Jeremy Y. Ng, Holger Cramer, Myeong Soo Lee, David Moher

“…AI may augment TCIM by assisting in early disease detection, providing personalized treatment plans, predicting health trends, and enhancing patient engagement. …”
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Comprehensive benchmarking of genome editing quantification methods for plant applications by Zheng Gong, Yan Zhang, Di Xia, Sohye Yoon, Peter Alexander Crisp, José Ramón Botella

“…We measured genome editing efficiency from 20 transiently expressed Cas9 targets using different techniques, including targeted amplicon sequencing (AmpSeq), PCR-restriction fragment length polymorphism (RFLP) assays, T7 endonuclease 1 (T7E1) assays, Sanger sequencing of amplicon products (deconvoluted and analyzed using three algorithms), PCR-capillary electrophoresis/InDel detection by amplicon analysis (PCR-CE/IDAA), and droplet digital PCR (ddPCR). …”
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IDENTIFICATION OF SMALL LAKES IN KAZAKHSTAN USING REMOTE SENSING DATA by Akmaral Tolepbayeva, Dinara Abiyeva, Roza Karagulova, Aigerim Tanbayeva, Zhanerke Sharapkhanova

“…However, challenges such as dense vegetation, high salinity, and the color of shallow lake bottoms led to some classification errors, highlighting the need for further refinement of automated algorithms. As a result, a list of small lakes in Kazakhstan with a surface area from 1 to 10 km2 was identified. …”
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Exploring Feature Selection with Deep Learning for Kidney Tissue Microarray Classification Using Infrared Spectral Imaging by Zachary Caterer, Jordan Langlois, Connor McKeown, Mikayla Hady, Samuel Stumo, Suman Setty, Michael Walsh, Rahul Gomes

“…This would create an advanced diagnostic tool for the detection and classification of renal tumors, namely chromophobe RCC and Oncocytoma. …”
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Pixel-Based Long-Wave Infrared Spectral Image Reconstruction Using a Hierarchical Spectral Transformer by Zi Wang, Yang Yang, Liyin Yuan, Chunlai Li, Jianyu Wang

“…Long-wave infrared (LWIR) spectral imaging plays a critical role in various applications such as gas monitoring, mineral exploration, and fire detection. Recent advancements in computational spectral imaging, powered by advanced algorithms, have enabled the acquisition of high-quality spectral images in real time, such as with the Uncooled Snapshot Infrared Spectrometer (USIRS). …”
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Early Warning of Nerve Agent Release in Large Indoor Environments Based on Encoder-Decoder Coupling Physics-Informed Neural Network by Shuobei Sun, Yang Peng, An Wang, Yiwen Xie, Yang Hu, Zhongyu Hou

“…Accurately perceiving spatial distribution patterns, detecting dynamic evolution characteristics, and issuing early warnings set higher standards for indoor safety and protection efforts. …”
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