Evaluation of the impact of COVID-19 on hepatitis B in Henan Province and its epidemic trend based on Bayesian structured time series model by Xinxiao Li, Yanyan Li, Shushuo Xu, Penghao Wang, Meng Hu, Haibin Li, Yongbin Wang

“…To assess how well the BSTS algorithm performs predictions, we split the observations into various training and testing ranges. …”
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Association of estimated glucose disposal rate with atrial fibrillation, heart failure and cardiovascular mortality in patients with diabetes: a prospective cohort study from the U... by Zhen Tan, Yijun Liu, Lei Liu, Shuang Li, Xinrui Xue, Xiaoping Li, Hongqiang Ren

“…Polygenic Risk Score (PRS) analysis evaluated the joint effects of eGDR and PRS. Boruta algorithm filtered key predictive variables. Subgroup analysis was performed using cardiovascular high-risk factors, and mediation analysis explored the relationships of eGDR with the outcomes.ResultsSubjects with higher eGDR were more likely to be female, younger, more physically active, non-smoker, and non-drinker. …”
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PDT-regulated immune gene prognostic model reveals tumor microenvironment in colorectal cancer liver metastases by Jiachi Xu, Hui Zhou, Zhongtao Liu, Yunpeng Huang, Zijian Zhang, Heng Zou, Yongxiang Wang

“…By using the weighted gene co-expression network analysis (WGCNA) algorithm, key gene modules related to metastasis in colorectal cancer were identified. …”
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Big data and AI for gender equality in health: bias is a big challenge by Anagha Joshi, Anagha Joshi, Anagha Joshi

“…Despite these promises, machine learning applications are not widely adapted in clinical care due to many issues including ethical concerns, patient privacy, informed consent, algorithmic biases, data quality and availability, and education and training of health care professionals. …”
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Integrating Multi-Variable Driving Factors to Improve Land Use & Land Cover Classification Accuracy using Machine Learning Approaches: A Case Study from Lombok Island by Miftahul Irsyadi Purnama, Hüseyin Oğuz Çoban

“…In field validation assessments, comparing the predictions of these machine learning models with ground truth data, Random Forest was the most reliable, achieving an overall accuracy of 88%. …”
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A Framework for Autonomous UAV Navigation Based on Monocular Depth Estimation by Jonas Gaigalas, Linas Perkauskas, Henrikas Gricius, Tomas Kanapickas, Andrius Kriščiūnas

“…The solution utilizes a depth image estimation model to create an occupancy grid map of the surrounding area and uses an A* path planning algorithm to find optimal paths to end goals while navigating around the obstacles. …”
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Challenges and opportunities to minimize the dose in the neurovascular bundles during prostate radiotherapy by Victor J. Brand, Linda Rossi, Maaike T.W. Milder, Femke E. Froklage, Alison C. Tree, Mischa S. Hoogeman, Luca Incrocci

“…All treatment plans (5 × 7.25 Gy) were automatically generated using Erasmus-iCycle (in-house automated treatment planning algorithm). Non-NVB sparing (non-NVBsparing) plans and NVB sparing plans in two settings were generated: (1) uncompromised NVB sparing (u-NVBsparing; maintaining target coverage) (2) and compromised NVB sparing (c-NVBsparing; allowing target underdosage). …”
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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

“…The findings contribute to cybersecurity efforts by comprehensively assessing machine learning algorithms for obfuscated malware detection through memory analysis. …”
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History of Location Objectives (Hilal Tracker): Development of Astronomical Observations from 2015-Present by Marataon Ritonga, Alya Fathi Muhammad Hasibuan, Rizqan Arya Perdana Nazara

“…This article explains the history of the development of hilal Tracker technology and methods, including integrating astronomical data, using satellite imagery, algorithms for predicting hilal visibility, and cooperation with various local and international institutions. …”
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Knowledge graph convolutional networks with user preferences for course recommendation by Zhong Hua, Jianbai Yang, Weidong Ji

“…Research on KG-enhanced recommendation algorithms has found that the utilization of side information in KGs is crucial for improving accuracy. …”
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AI-Driven Gamification and Biotechnical Systems in Cardiovascular Monitoring of Cyclic Sport Athletes by Shukurova Sayyora, Pulatova Mavlyuda, Adilbekov Taxir

“…The paper attempts to move forward research in biotechnical systems and gamification from traditional sports medicine, athlete conditioning, and exercise physiology contexts to emerging AI-enhanced frameworks that address current cardiovascular health challenges.In proposing such a novel approach, the authors reason why AHP-regression-based studies may be particularly suited for the iterative assessment, validation, and optimization of findings in the form of decision-making models such as personalized AI-driven training algorithms. Additionally, the analytical hierarchy process (AHP) framework is used to organize a systematic evaluation of predictive modeling techniques to identify some best practices related to specific biométrie parameters and athlete performance metrics.This methodological application then furthers the examination of the physiological and computational implications related to the use of AI-driven cardiovascular monitoring in terms of accuracy, efficiency, and adaptability. …”
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Building a composition-microstructure-performance model for C–V–Cr–Mo wear-resistant steel via the thermodynamic calculations and machine learning synergy by Shuaiwu Tong, Shuaijun Zhang, Chong Chen, Tao Jiang, Peng Li, Shizhong Wei

“…Furthermore, feature importance analysis, conducted using the Random Forest algorithm, revealed significant differences in the factors affecting sliding friction and abrasive wear. …”
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FPGA Implementation for 24.576-Gbit/s Optical PAM4 Signal Transmission with MLP-Based Digital Pre-Distortion by Sheng Hu, Tianqi Zheng, Chengzhen Bian, Xiongwei Yang, Xinda Sun, Zonghui Zhu, Yumeng Gou, Yuanxiao Meng, Jie Zhang, Jingtao Ge, Yichen Li, Kaihui Wang

“…Lookup table (LUT) algorithms are commonly employed for pre-distortion in intensity modulation and direct detection (IM/DD) systems. …”
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Cervical cancer screening uptake and its associated factor in Sub-Sharan Africa: a machine learning approach by Fetlework Gubena Arage, Zinabu Bekele Tadese, Eliyas Addisu Taye, Tigist Kifle Tsegaw, Tsegasilassie Gebremariam Abate, Eyob Akalewold Alemu

“…These algorithms were employed to predict cervical cancer screening uptake. …”
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Autoconcepto físico en estudiantes universitarios: Generación de perfiles por clasificación jerárquica sobre componentes principales (Physical self-concept in university students:... by Luis Alberto Cardozo, Jhonatan C. Peña-Ibagón, Widad Florez-Escobar, Carlos A. Castillo-Daza, Diego A. Bonilla-Ocampo, Javier L. Reina-Monroy

“…The aims of this study were i) to analyze and compare the physical self-concept in university students considering possible differences between sexes and associations with socioeconomic status and age, and ii) to generate student profiles using unsupervised machine learning algorithms. A total of 230 Colombian students between 18 and 38 years of age from the Physical Education (n = 118) and Psychology (n = 112) majors participated in this cross-sectional study. …”
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Performance of the Oncuria-Detect bladder cancer test for evaluating patients presenting with haematuria: results from a real-world clinical setting by Ian Pagano, Zhen Zhang, Michael Luu, Sergei Tikhonenkov, Florence Le Calvez-Kelm, Steve Goodison, Toru Sakatani, Kaoru Murakami, Takashi Kobayashi, Patrice Avogbe, Howard Kim, Riko Lee, Arnaud Manel, Emmanuel Vian, Charles J. Rosser, Hideki Furuya

“…Methods We tested prospectively collected urine samples from a real-world cohort of 931 patients presenting to five US centres, one European centre and one Japanese centre with haematuria, in addition to 69 patients with either kidney or prostate cancer (disease controls). The algorithm training/refinement set comprised 617 subjects and the test set included 383 subjects. …”
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Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems by Yongxin Li, Ali Basem, As'ad Alizadeh, Pradeep Kumar Singh, Saurav Dixit, Hanaa Kadhim Abdulaali, Rifaqat Ali, Pancham Cajla, Husam Rajab, Kaouther Ghachem

“…MOO based on GMDH-NN models using the novel multi-objective thermal exchange optimization (MOTEO) algorithm revealed trade-offs: maximizing EP and TP increased EG, highlighting inherent inefficiencies. …”
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Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders by Xiaoman Xing, Sizhi Ai, Jihui Zhang, Rui Huang, Yaping Liu, Dongming Quan, Jiacheng Ma, Guoli Wu, Jiangen Xu, Yuan Zhang, Hongliang Feng, Wen-fei Dong

“…Apex-centric tokenization enhances sensitivity to OSA events, while MHCA refines predictions and increases specificity in detecting oxygen desaturation. …”
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Clinical-oriented 3D visualization and quantitative analysis of gingival thickness using convolutional neural networks and CBCT by Lan Yang, Lan Yang, ZiCheng Zhu, Yongshan Li, Jieying Huang, Xiaoli Wang, Haoran Zheng, Jiang Chen

“…The intuitive 3D visualization serves as an innovative preoperative tool that identifies high-risk areas and guides personalized surgical planning, enhancing predictability for aesthetic and complex implant cases.…”
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The Mass of the Vela Pulsar Progenitor and the Age of the Vela-Puppis Complex by Jeremiah W. Murphy, Andrés F. Barrientos, René Andrae, Joseph Guzman, Benjamin F. Williams, Julianne J. Dalcanton, Brad Koplitz

“…Gaia parallaxes and Stellar Ages enable these results; Stellar Ages is a novel stellar population modeling algorithm that combines individual and population-level age inferences.…”
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