DBSCAN-PCA-INFORMER-Based Droplet Motion Time Prediction Model for Digital Microfluidic Systems by Zhijie Luo, Bin Zhao, Wenjin Liu, Jianhua Zheng, Wenwen Chen

“…This study records data using a machine vision-based digital microfluidic driving control system. …”
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Ensemble learning techniques reveals multidimensional EEG feature alterations in pediatric schizophrenia by Ying Mao, Ying Mao, Fang Wang, Shan Wang, Zhaowei Wang, Gang Li, Xuchen Qi, Xuchen Qi, Yu Sun, Yu Sun

“…Particularly, altered FCs exhibited a fronto-increase-parieto-decrease pattern mainly in the right hemisphere along with spectral-dependent RP alterations and a universally reduced FuzEn in the pediatric SCZ group. …”
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Leveraging Artificial Intelligence and Data Science for Integration of Social Determinants of Health in Emergency Medicine: Scoping Review by Ethan E Abbott, Donald Apakama, Lynne D Richardson, Lili Chan, Girish N Nadkarni

“…Rule-based NLP (n=5), deep learning (n=2), and pattern matching (n=4) were the most commonly used NLP techniques. …”
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Analyzing Patient Complaints in Web-Based Reviews of Private Hospitals in Selangor, Malaysia, Using Large Language Model–Assisted Content Analysis: Mixed Methods Study by Muhammad Hafiz Sulaiman, Nora Muda, Fatimah Abdul Razak

“…Fake reviews were filtered out using natural language processing and machine learning algorithms trained on yelp.com validated datasets. …”
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Dataset creation of thermal images of pomegranate for internal defect detectionMendeley Data by Ashvini Gaikwad, Manoj Deshpande, Varsha Bhole

“…This information is useful for training a machine learning algorithms that are intended for bulk processing in the field of fruit defect detection and classification.…”
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An upgraded high-precision gridded precipitation dataset for the Chinese mainland considering spatial autocorrelation and covariates by J. Hu, C. Miao, J. Su, Q. Zhang, J. Gou, J. Gou, Q. Sun, Q. Sun

“…Building upon the improved inverse distance weighting interpolation method used in our previous dataset CHM_PRE V1, we integrated a machine learning algorithm – light gradient boosting machine (LGBM) – to incorporate precipitation-related covariates in a data-driven manner. …”
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Integrated Platform for Bio-Image Processing and Identification of Cervical Cancer by Larisa-Dalina LAZĂR, Diogen BABUC, Todor IVAŞCU

“…Following this, the cervical cells are segmented and classified using a combination of machine learning algorithms, such as shallow machine learning models and Convolutional Neural Networks (CNN). …”
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Precise irrigation of dryland cotton under canal irrigation system constraints based on the CERES-CROPGRO-Cotton model by Lei Wang, Liang He, Weihong Sun, Chen Gao, Zhenxiang Han, Meiwei Lin

“…Existing studies primarily examine the relationship between irrigation and soil but often overlook the combined effects of irrigation networks, time constraints, and the interactions between crop growth patterns, weather, soil, and irrigation strategies. …”
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High-throughput discovery of genetic determinants of circadian misalignment. by Tao Zhang, Pancheng Xie, Yingying Dong, Zhiwei Liu, Fei Zhou, Dejing Pan, Zhengyun Huang, Qiaocheng Zhai, Yue Gu, Qingyu Wu, Nobuhiko Tanaka, Yuichi Obata, Allan Bradley, Christopher J Lelliott, Sanger Institute Mouse Genetics Project, Lauryl M J Nutter, Colin McKerlie, Ann M Flenniken, Marie-France Champy, Tania Sorg, Yann Herault, Martin Hrabe De Angelis, Valerie Gailus Durner, Ann-Marie Mallon, Steve D M Brown, Terry Meehan, Helen E Parkinson, Damian Smedley, K C Kent Lloyd, Jun Yan, Xiang Gao, Je Kyung Seong, Chi-Kuang Leo Wang, Radislav Sedlacek, Yi Liu, Jan Rozman, Ling Yang, Ying Xu

“…By collecting and analyzing indirect calorimetry (IC) data from more than 2000 wild-type mice available from the International Mouse Phenotyping Consortium (IMPC), we show that the onset time and peak phase of activity and food intake rhythms are reliable parameters for screening defects of circadian misalignment. We developed a machine learning algorithm to quantify these two parameters in our misalignment screen (SyncScreener) with existing datasets and used it to screen 750 mutant mouse lines from five IMPC phenotyping centres. …”
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Study on the mechanisms associating community outdoor public spaces with elderly behavior by Lei Wang, Wenqi He, Shan Wu, Bo Zhang, Xiaorui Zhang, Hu Yin

“…This research delves into the intricate relationship between community outdoor public spaces and the behavioral patterns of the elderly, seeking to inform strategies for optimizing these spaces. …”
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AI-Driven Ensemble Classifier for Jamming Attack Detection in VANETs to Enhance Security in Smart Cities by Walid El-Shafai, Ahmad Taher Azar, Saim Ahmed

“…Its primary aim is the effective identification of anomalous patterns signaling the presence of jamming attacks. …”
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Novel insights into the molecular mechanisms of sepsis-associated acute kidney injury: an integrative study of GBP2, PSMB8, PSMB9 genes and immune microenvironment characteristics by Haiting Ye, Xiang Zhang, Pengyan Li, Mei Wang, Ruolan Liu, Dingping Yang

“…The expression patterns of these three genes were well-validated through animal experiments and databases. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
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A Multivariate Phenotypical Approach of Sepsis and Septic Shock—A Comprehensive Narrative Literature Review by Alina Tita, Sebastian Isac, Teodora Isac, Cristina Martac, Geani-Danut Teodorescu, Lavinia Jipa, Cristian Cobilinschi, Bogdan Pavel, Maria Daniela Tanasescu, Liliana Elena Mirea, Gabriela Droc

“…Given the heterogeneity of sepsis and recent technological progress amongst machine learning analysis techniques, a new, personalized approach to sepsis is being intensively studied. …”
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Spatiotemporal variation of the association between climate dynamics and HFRS outbreaks in Eastern China during 2005-2016 and its geographic determinants. by Junyu He, George Christakos, Jiaping Wu, Bernard Cazelles, Quan Qian, Di Mu, Yong Wang, Wenwu Yin, Wenyi Zhang

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Using Digital Phenotyping to Discriminate Unipolar Depression and Bipolar Disorder: Systematic Review by Rongrong Zhong, XiaoHui Wu, Jun Chen, Yiru Fang

“…For each included study, the following information was extracted: demographic characteristics, diagnostic criteria or psychiatric assessments, details of the technological tools and data types, duration of data collection, data preprocessing methods, selected variables or features, machine learning algorithms or statistical tests, validation, and main findings. …”
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Acute Respiratory Infections Identification With Cough Sounds and Overlapping Patch Modulated Vision Transformers by P. V. V. Kishore, D. Anil Kumar, Pasupuleti Sasikiran, Kaja Krishna Mohan, P. Praveen Kumar, Mogadala Vinod Kumar

“…Variable cough sound vs silent intervals between samples of a class in MFCC spectral images has shown to influence training algorithms to learn meaningful patterns for classification. …”
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Classification of left and right-hand motor imagery in acute stroke patients using EEG microstate by Shiyang Lv, Xiangying Ran, Mengsheng Xia, Yehong Zhang, Ting Pang, Xuezhi Zhou, Zongya Zhao, Yi Yu, Zhixian Gao

“…Significant features were used to construct classification models using Linear Discriminant Analysis(LDA), Support Vector Machines(SVM), and K-Nearest Neighbors(KNN) algorithms. …”
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Interpreting neural decoding models using grouped model reliance. by Simon Valentin, Maximilian Harkotte, Tzvetan Popov

“…Machine learning algorithms are becoming increasingly popular for decoding psychological constructs based on neural data. …”
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Image masks of global ship tracks for NASA MODIS data products by Pierce Warburton, Kurtis Shuler, Jake P. Zenker, Lekha Patel

“…Established from a previous dataset that identified ship track presence using NASA’s MODIS Aqua satellite imager, our first-of-its-kind dataset is comprised of image masks: capturing full ship track regions, including their contours, emission points and dispersive patterns. In total, 300 images, or around 2,500 masked ship tracks, observed under varying conditions are provided, and may facilitate training of machine learning algorithms to automate extraction.…”
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