Real-Time Anomaly Detection in IoMT Networks Using Stacking Model and a Healthcare- Specific Dataset by Hadjer Goumidi, Samuel Pierre

“…Seven machine learning algorithms, including Random Forest, XGBoost, and Artificial Neural Networks (ANN), were rigorously tested, leading to the development of a novel stacking ensemble model. …”
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Fostemsavir resistance in clinical context: a narrative review by Jonathan M. Schapiro, Rolf Kaiser, Mark Krystal, Chris M. Parry, Allan R. Tenorio, Eugene Stewart, Bruce Gilliam, Margaret Gartland, Andrew Clark, Jose R. Castillo-Mancilla

“…Due to these factors and limited phenotypic clinical data, thus far, no relevant phenotypic cutoff or genotypic algorithms have been derived that reliably predict response to fostemsavir-based therapy in individuals who are HTE; therefore, pre-treatment temsavir resistance testing may be of limited benefit. …”
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Determination of high-confidence germline genetic variants in next-generation sequencing through machine learning models: an approach to reduce the burden of orthogonal confirmatio... by Muqing Yan, Qiandong Zeng, Zhenxi Zhang, Patricia Okamoto, Stanley Letovsky, Angela Kenyon, Natalia Leach, Jennifer Reiner

“…Improvements to early NGS methods and bioinformatics algorithms have dramatically improved variant calling accuracy, particularly for single nucleotide variants (SNVs), thus calling into question the necessity of confirmatory testing for all variant types. …”
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Performance Statistics of Autoregressive Short and Ultrashort Signal Detectors by V. M. Kutuzov, V. P. Ipatov, S. S. Sokolov

“…The obtained detection and noise immunity characteristics for ultrashort and short signal samples allow us to recommend the parametric Burg harmonic mean method, implemented on the basis of a forward and backward linear prediction algorithm, as an independent signal processing method under strict restrictions imposed on the size of the analyzed sample of spatial-temporal signals.…”
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Porcine Ovarian piRNA Dynamics: A Comparative Study During Follicular Atresia by Jinbi Zhang, Long Huang, Xinxin Qin, Wenjie Li, Xiaolong Cheng, Zengxiang Pan

“…The target genes of differentially expressed piRNAs were predicted and subjected to functional analysis. A total of 452 piRNAs were identified across all samples, with 103 showing differential expression between HFs and AFs. …”
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Optimization of diagnostics of retinopathy of prematurity stages based on the integration of clinical data using the Key to Diagnosis I software by O. A. Pererva, M. A. Kovalevskaya

“…Despite the improvement of algorithms of preterm infants’ management, methods for predicting, diagnosing and treating ROP remains a vital issue.   …”
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Exploring the binding potential of natural compounds to carbonic anhydrase of cyanobacteria through computer-based simulations by Archana Padhiary, Showkat Ahmad Mir, Aiswarya Pati, Binata Nayak

“…Strategically we explore the Structural-Activity Relationship (SAR) of natural compounds to the reported sulphonamide inhibitors. Further, prediction-based online web servers such as pkCSM and SwissADME were used to determine the ADMET properties of the SAR molecules. …”
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Real Time Intrusion Detection System Based on Web Log File Analysis by Rawand Raouf Abdalla, Alaa Khalil Jumaa, Ahmad Freidoon Fadhil

“…In this paper, we developed a real time IDS based on weblog analysis which is used to predict if the user’s request is an attack, normal, or suspicious. …”
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Enhancing healthcare with AI: Sustainable AI and IoT-Powered ecosystem for patient aid and interpretability analysis using SHAP by Biplov Paneru, Bishwash Paneru, Sanjog Chhetri Sapkota, Ramhari Poudyal

“…The cloud-stored data can be harnessed to ascertain and supervise one's health and predict forthcoming perils. This study unveils an efficacious decision-making model custom-tailored for Internet of Things (IoT) ventures, and the proposed trained algorithm satiates these requirements, offering efficiency and precision, rendering it appropriate for numerous IoT applications. …”
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Bioinformatics analysis of intrinsic drivers of immune dysregulation in multiple myeloma to elucidate immune phenotypes and discover prognostic gene signatures by Chuan-Feng Fang, Yan Li, Chun Yang, Hua Fang, Chen Li

“…Prognostic Gene Signature: Ten immune-related genes (UBE2T, E2F2, EXO1, SH2D2A, DRP2, WNT9A, SHROOM3, TMC8, CDCA7, and GPR132) predicted survival (The One-year AUC = 0.682 and The Over 5-years AUC = 0.714). …”
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Technological Advancements in Human Navigation for the Visually Impaired: A Systematic Review by Edgar Casanova, Diego Guffanti, Luis Hidalgo

“…Current navigation algorithms were also identified in the review with methods including obstacle detection, path planning, and trajectory prediction, applied to technologies such as ultrasonic sensors, RGB-D cameras, and LiDAR for indoor navigation, as well as stereo cameras and GPS for outdoor navigation. …”
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Transfer Learning based Image Classification of Diseased Tomato Leaves with Optimal Fine-Tuning combined with Heat Map Visualization by Sivakumar Palanıswamy, Vijayakumar Vaıthyam Rengarajan, Sandhya Devi Ramıah Subburaj

“…It is presumed that the implementation of deep learning algorithms demands a large amount of data to learn complex features automatically and this can pose a challenge for applications with lesser data to achieve generalization. …”
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Macro-Modelling of Rib-Knitted Tubular Parts by Tetiana Ielina, Liudmyla Halavska, Nataliia Ausheva

“…The use of modern software helps us predict the physical and mechanical behaviour of materials, using their three-dimensional models. …”
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Performance Analysis of Real-Time Detection Transformer and You Only Look Once Models for Weed Detection in Maize Cultivation by Oscar Leonardo García-Navarrete, Jesús Hernán Camacho-Tamayo, Anibal Bregon Bregon, Jorge Martín-García, Luis Manuel Navas-Gracia

“…To reduce the influence of weeds, precision weeding is used, which uses image sensors and computational algorithms to identify plants and classify weeds using digital images. …”
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Comprehensive optimization of passenger trains operation based on an automated system for managing the profitability of passenger traffic by G. L. Venediktov, V. M. Kochetkov

“…Developed models make it possible to form optimal train schemes in accordance with the predicted demand, balancing supply and demand for transportation, which, in turn, radically increases its economic efficiency. …”
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Determination of indications for the choice of the preparation method of the root canal system with rotation and reciprocation instruments by I. V. Pyatkova, L. Yu. Orekhova, T. V. Porkhun, A. V. Silin

“…Compliance with the algorithms of endodontic treatment in most cases ensures the quality of treatment. …”
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Landslide Hazard Assessment Under Record-Breaking Extreme Rainfall: Integration of SBAS-InSAR and Machine Learning Models by Wenbo Zheng, Wen Fan, Yanbo Cao, Yalin Nan, Pengxu Jing

“…The proposed framework integrates cumulative extreme rainfall metrics with subtle ground deformation indicators and applies four advanced machine learning algorithms—DNN, XGBoost, RF, and LightGBM—for multidimensional hazard assessment. …”
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Integrative bioinformatics analysis and experimental validation of key biomarkers driving the progression of cirrhotic portal hypertension by Meilin Li, Lilin Jiang, Yunrui Ru, Zhonghua Lu, Peng Gu

“…The aim of this study was to identify hub genes for predicting persistent progression of portal hypertension in patients with liver cirrhosis. …”
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Air Pollution Forecasting Using Artificial and Wavelet Neural Networks with Meteorological Conditions by Qingchun Guo, Zhenfang He, Shanshan Li, Xinzhou Li, Jingjing Meng, Zhanfang Hou, Jiazhen Liu, Yongjin Chen

“…Additionally, the API could be accurately predicted based solely on the value recorded 3 days earlier. …”
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Field Validation of the DNDC-Rice Model for Crop Yield, Nitrous Oxide Emissions and Carbon Sequestration in a Soybean System with Rye Cover Crop Management by Qiliang Huang, Nobuko Katayanagi, Masakazu Komatsuzaki, Tamon Fumoto

“…These findings indicate that the DNDC-Rice model requires improvements in its N cycling algorithm and crop growth sub-models to improve predictions for upland systems. …”
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