Enhancing Mild Cognitive Impairment Auxiliary Identification Through Multimodal Cognitive Assessment with Eye Tracking and Convolutional Neural Network Analysis by Na Li, Ziming Wang, Wen Ren, Hong Zheng, Shuai Liu, Yi Zhou, Kang Ju, Zhongting Chen

“…<b>Conclusions</b>: Results show that a multimodal model significantly outperforms single-feature models in identifying MCI, highlighting the potential of eye-tracking for early detection. These findings suggest that integrating multimodal data can enhance the effectiveness of MCI auxiliary identification, providing a novel potential pathway for community-based early detection efforts.…”
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High-energy dual-energy computed tomography for the characterization of large and thick objects by Alix Sardet, Daniel Eck, Nicolas Estre, Frédéric Moutet, Emmanuel Payan, Cécilia Tarpau

“…Conventional dual-energy computed tomograohy (DECT) techniques are: (a) pre-processing dual-energy data sets and performing conventional CT reconstruction [1], (b) reconstruct dual-energy data sets and analyse the ratio of obtained linear attenuation coefficients [2, 3] and (c) reconstruct data sets after a decomposition on a material basis [4-6]. …”
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Simulation of IoT Smart Home Network with Decision Making Based on MajorDoMo Platform by U. A. Vishniakou, ChuYue Yu

“…The possibilities of the PHP language for the implementation of the control process are presented, in which the household device begins to adjust the parameters when the environmental monitoring system detects that the corresponding data exceeds the set threshold.…”
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“VTMine for Visio”: Graphical Tool for Modeling in Process Mining by Sergey A. Shershakov

“…There are presented features of the architecture design of the software extension for application in the process mining domain and integration with the existing libraries and tools for working with data. The application of the developed tool for solving various types of tasks for modeling and analysis of processes is demonstrated on a set of experimental schemes.…”
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Implications of machine learning techniques for prediction of motor health disorders in Saudi Arabia by Ehab M. Almetwally, I. Elbatal, Mohammed Elgarhy, Amr R. Kamel

“…The dataset was partitioned into a training set comprising 70 % of the data and a testing set containing 30 % of the data using the ML algorithms. …”
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Diagnosis of Tuberculous Pericarditis in Zhejiang, China: A Diagnostic Prediction Model Based on LASSO Logistic Regression by Xu X, Liu X, Yang C, Cai L, Liu L, Chen T, Zhu H, Wei H

“…DCA results indicated that the model has significant clinical application value when the threshold probability is set between 1– 100% (training set) and 30– 100% (validation set).Conclusion: We successfully developed a nomogram model for predicting tuberculous pericarditis, which can assist clinicians in improving diagnostic accuracy and reducing misdiagnoses and missed diagnoses in primary healthcare settings.Plain Language Summary: Imagine you have a tool that helps doctors figure out if someone has a serious heart issue called tuberculous pericarditis, which is tough to detect. …”
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Laser Frequency Noise Cancelation in a Phase-Shifted Fiber Bragg Grating Ultrasonic Sensor System Using a Reference Grating Channel by Lingling Hu, Guigen Liu, Yupeng Zhu, Xiangyu Luo, Ming Han

“…Employing a data postprocessing method, the noise is subtracted from the original detected signal. …”
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DNA familial binding profiles made easy: comparison of various motif alignment and clustering strategies. by Shaun Mahony, Philip E Auron, Panayiotis V Benos

“…This work provides a high quality reference set of familial binding profiles and the first comprehensive platform for analysis of DNA profiles. …”
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Exploring potential methylation markers for ovarian cancer from cervical scraping samples by Ju-Yin Lien, Lu Ann Hii, Po-Hsuan Su, Lin-Yu Chen, Kuo-Chang Wen, Hung-Cheng Lai, Yu-Chao Wang

“…Methylation data were initially divided into training and testing sets in a 3:1 ratio comprising 120 and 40 samples, respectively. …”
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Research on COP Prediction Model of Chiller Based on PSO-SVR by Zhou Xuan, Cai Panpan, Lian Sizhen, Yan Junwei

“…Since the difficulty of building mechanism model and the structure of COP model of chiller is complex, greatly affected by operating parameter, a COP prediction model of chiller is proposed based on Support Vector Regression, and the parameters are optimized by Particle Swarm Optimization algorithm. In this paper, 396 sets of operating data of chiller of a shopping mall are randomly selected to train and test this model. …”
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Predicting future occlusion or stenosis of lower extremity bypass grafts using artificial intelligence to simultaneously analyze all flow velocities collected in current and previo... by Xiao Luo, PhD, Fattah Muhammad Tahabi, BS, Dave M. Rollins, RVT, Alan P. Sawchuk, MD

“…We excluded the examinations with missing values and split our data into training and test sets. Then, we applied 10-fold cross-validation on training to optimize the hyperparameters and compared models using the test data. …”
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A Kind of Dynamic Clustering Algorithm Based on Angle Measurement by HE Yun bin, SUN Nuan, WAN Jing, LI Song

“…The experimental results show that this algorithm can effectively process various data sets for increasing data.…”
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Whitelists Based Multiple Filtering Techniques in SCADA Sensor Networks by DongHo Kang, ByoungKoo Kim, JungChan Na, KyoungSon Jhang

“…In this paper we propose a multiple filtering technique based on whitelists to detect illegitimate packets. Our proposed system detects the traffic of network and application protocol attacks with a set of whitelists collected from normal traffic.…”
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The Global Prevalence of <i>Bacillus</i> spp. in Milk and Dairy Products: A Systematic Review and Meta-Analysis by Tianmei Sun, Ran Wang, Yanan Sun, Xiaoxu Zhang, Chongtao Ge, Yixuan Li

“…Following the principles of systematic review, 417 sets of prevalence data were extracted from 142 eligible publications. …”
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Validation of Replicable Pipeline 3D Surface Reconstruction for Patient-Specific Abdominal Aortic Lumen Diagnostics by Edoardo Ugolini, Giorgio La Civita, Moad Al Aidroos, Samuele Salti, Giuseppe Lisanti, Emanuele Ghedini, Gianluca Faggioli, Mauro Gargiulo, Giovanni Rossi

“…<b>Results:</b> The test set is selected to cover a wide portion of aortoiliac pathologies. …”
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Deep source separation of overlapping gravitational-wave signals and nonstationary noise artifacts by Niklas Houba

“…By learning clustered latent-space representations, the framework provides a scalable alternative to conventional methods, with applications in both low-latency event detection and full-scale global-fit analyses. As a proof-of-concept, we assess the model's performance using simulated LISA data in a controlled setting with a limited number of overlapping sources. …”
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An interpretable machine learning approach for predicting and grading hip osteoarthritis using gait analysis by Qing Yang, Xinyu Ji, Yuyan Zhang, Shaoyi Du, Bing Ji, Wei Zeng

“…Although various interventions have been designed to alleviate these symptoms, it is unclear if there is a reliable method to track biomechanical changes in patients with unilateral hip OA in a clinical setting. Purpose The purpose of this study is to evaluate the efficacy of lower extremity kinematic gait data for detecting and rating the severity of unilateral hip OA using machine learning algorithms. …”
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Validating the Orbital Periods of the Coolest TESS Planet Candidates by Dillon J. Bass, Daniel C. Fabrycky

“…We present these TESS Objects of Interest, along with a variety of small corrections to other TESS orbital periods and three planet candidates with possible transit timing variations, with the goal of refining the TESS data set and enabling future research with respect to cool transiting planets.…”
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Global knowledge gaps in acute febrile illness etiologic investigations: A scoping review. by Chulwoo Rhee, Grishma A Kharod, Nicolas Schaad, Nathan W Furukawa, Neil M Vora, David D Blaney, John A Crump, Kevin R Clarke

“…These steps can guide resource allocation, strengthen outbreak detection and response, target prevention efforts, and improve clinical care, especially in resource-limited settings where disease control often relies on empiric treatment. …”
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Photogrammetry engaged automated image labeling approach by Jonathan Boyack, Jongseong Brad Choi

“…Deep learning models require many instances of training data to be able to accurately detect the desired object. …”
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