Data-Driven Prediction of Grape Leaf Chlorophyll Content Using Hyperspectral Imaging and Convolutional Neural Networks by Minglu Zeng, Xinghui Zhu, Ling Wan, Jian Xu, Luming Shen

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Quantifying Lenition as a Diagnostic Marker for Parkinson’s Disease and Atypical Parkinsonism by Ratree Wayland, Rachel Meyer, Ruhi Reddy, Kevin Tang, Karen W. Hegland

“…<b>Methods:</b> Using Phonet, a machine learning model trained to detect phonological features, we analyzed the posterior probabilities of continuant and sonorant features from the speech of 142 participants (108 PD, 34 APD). …”
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Application of Simulated Annealing Algorithm in the Construction of Online Examination System for Tax Law Courses by da Pan

“…This study proposes a simulated annealing (SA)-based optimization model for dynamically generating balanced online examinations in tax law courses. …”
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Design and implementation of quantum hippo inspired convolutional neural networks using parametric quantum circuits for an efficient lung cancer classification by S. Radhika, G. Sharada

“…The proposed learning framework consists of four components namely Data collection & Data pre-processing, Classical Hippo Optimized Convolutional Neural networks, and Quantum based model using parametric quantum circuits (PQC), Evaluation and Analysis. …”
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Numerical analysis on performance evaluation of photovoltaic thermal systems using ternary hybrid nanofluids and forced convection around copper cylinders by Maha Alammari, Gul M. Shaikh, Abid A. Memon, T.H. El-Ghareeb, Amsalu Fenta

“…The aspect ratio in this study is defined as the ratio of the height of a square obstacle within the flow channel to the total height of the flow channel. A supervised machine learning framework develops predictive regression models for system analysis. …”
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Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study by Océane Dorémus, Dylan Russon, Benjamin Contrand, Ariel Guerra-Adames, Marta Avalos-Fernandez, Cédric Gil-Jardiné, Emmanuel Lagarde

“…Initially, the journey toward protecting patient data deidentification saw the transition from rule-based systems to more mixed approaches including machine learning for deidentifying patient data. Subsequently, the emergence of large language models has represented a further opportunity in this domain, offering unparalleled potential for enhancing the accuracy of context-sensitive deidentification. …”
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Dynamics of street environmental features and emotional responses in urban areas: implications for public health and sustainable development by Yangfei Huang, Yangfei Huang, Chenjian Zhong, Chenjian Zhong, Tangtao He, Yuyang Jiang

“…Beyond this range, further increases in the GVI did not result in significant emotional changes.DiscussionThis study demonstrates the feasibility of predicting public emotional responses from street view images using machine learning. Optimizing green spaces and improving pedestrian environments can promote emotional health. …”
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Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

“…Feature selection and classification were performed using the Random Forest machine learning algorithm, optimized to identify the most predictive GM regions.ResultsOut of 114 GM regions, eleven were selected as optimal predictors: left angular gyrus, frontal operculum, occipital fusiform gyrus, parietal operculum, postcentral gyrus, planum polare, superior temporal gyrus, and right hippocampus, orbital part of the inferior frontal gyrus, posterior cingulate gyrus, and posterior orbital gyrus. …”
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Moanna: Multi-Omics Autoencoder-Based Neural Network Algorithm for Predicting Breast Cancer Subtypes by Richard Lupat, Rashindrie Perera, Sherene Loi, Jason Li

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Improving SMART learning: Course completion via AI-driven hybrid system integration in big data by Abdellah Bakhouyi, Amine Dehbi, Lahcen Amhaimar, Said Broumi, Mohamed Talea, Abderrahim Khalidi

“…This dissertation is about the development of an AI-enabled hybrid system that smartly leverages big data with the objective of optimizing course completion. The hybrid system implements state-of-the-art machine learning modeling techniques, including Decision Trees, Support Vector Machines, and Naïve Bayesian Classifiers for analyzing the performance of the students' data as well as for predicting successful completion of the course. …”
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A fault diagnosis method for inter-turn short circuit based on magnetic field distribution by Bowen Wang, Lulu Wang

“…This paper proposes a magnetic-electrical spatial state model that links local fault currents to leakage magnetic field variations. …”
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Genomics vs. AI-enhanced electrocardiogram: predicting atrial fibrillation in the era of precision medicine by Jean-Marie Grégoire, Cédric Gilon, François Marelli, Hugues Bersini, Stéphane Carlier

“…Artificial intelligence (AI) has emerged as a vital tool in predicting and detecting AF, with machine learning (ML) models trained on electrocardiogram (ECG) data now capable of identifying high-risk patients or predicting the imminent onset of AF. …”
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Let’s get in sync: current standing and future of AI-based detection of patient-ventilator asynchrony by Thijs P. Rietveld, Björn J. P. van der Ster, Abraham Schoe, Henrik Endeman, Anton Balakirev, Daria Kozlova, Diederik A. M. P. J. Gommers, Annemijn H. Jonkman

“…Last, prospective integration and model testing/finetuning in different ICU settings is key. …”
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rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

“…Temperature readings are labeled and stored for analysis, while audio data is classified into breathing, coughing, and speaking categories using the Support Vector Machine (SVM) algorithm. The SVM’s performance is further optimized using the Lion Algorithm. …”
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Single-cell and multi-omics analysis reveals the role of stem cells in prognosis and immunotherapy of lung adenocarcinoma patients by Jianan Zheng, Haoran Lin, Wei Ye, Mingjun Du, Chenjun Huang, Jun Fan

“…Patterns of immune infiltration were assessed using various computational approaches and were further validated in an internal hospital cohort.ResultsThrough comprehensive machine learning optimization, CoxBoost+Enet (alpha=0.7) was identified as the optimal model, incorporating seven key stem cell–related genes and designated as the Stem Cell Prognostic Model (SCPM). …”
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Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods by Ahmet Emre Ergun, Ozgu Can, Murat Kantarcioglu

“…Additionally, the Decision Tree (DT), Random Forest (RF), k-Nearest Neighbors (kNN), and GRU classification algorithms are also evaluated and compared with the XGBoost and LSTM classifiers for the proposed attack model. As a defense mechanism, DP is applied using the Fourier Perturbation Algorithm (FPA) to optimize padding strategies while maintaining network efficiency. …”
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Association between pro-inflammatory diet and fecal incontinence: a large population-based study by Haiyang Wang, Haiyang Wang, Zihan Liu, Zihan Liu, Xingfu Lu, Enyu Luan, Enyu Luan, Tingting Dong, Tingting Dong, Can Li, Can Li, Yanni Lv, Erkang Wu, Tao Shen, Tao Shen

“…BackgroundIt is widely acknowledged that dietary habits play a pivotal role in maintaining optimal intestinal health. Fecal incontinence (FI) is a distressing and often stigmatized inflammatory ailment with a strong correlation to a multitude of intestinal disorders. …”
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A systematic review of deep learning applications in database query execution by Bogdan Milicevic, Zoran Babovic

“…We categorize these approaches into three groups based on how such models are applied: improving performance of index structures and consequently data manipulation algorithms, query optimization tasks, and externally controlling query optimizers through parameter tuning. …”
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CTV-MIND: A cortical thickness-volume integrated individualized morphological network model to explore disease progression in temporal lobe epilepsy by Xinyan Liu, Jiaqi Han, Xiating Zhang, Boxuan Wei, Lu Xu, Qilin Zhou, Yuping Wang, Yicong Lin, Jicong Zhang

“…Incorporating identified network features into a machine learning-based brain age prediction model further revealed significantly elevated brain age in TLE. …”
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Working Element of a Horizontal Conveyor Type for Grass Raking by P. A. Eremin, V. V. Mikheev, A. Kh. Tekushev, M. Yu. Kostenko, V. P. Eremin

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