GEM-CRAP: a fusion architecture for focal seizure detection by Jianwei Shi, Yuanyuan Zhang, Ziang Song, Hang Xu, Yanfeng Yang, Lei Jin, Hengxin Dong, Zhaoying Li, Penghu Wei, Yongzhi Shan, Guoguang Zhao

“…Abstract Background Identification of seizures is essential for the treatment of epilepsy. Current machine-learning and deep-learning models often perform well on public datasets when classifying generalized seizures with prominent features. …”
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LYN and CYBB are pivotal immune and inflammatory genes as diagnostic biomarkers in recurrent spontaneous abortion by Zhuna Wu, Qiuya Lin, Zhimei Zhou, Yajing Xie, Li Huang, Liying Sheng, Qirong Shi, Yumin Ke

“…We further confirmed the expression levels and diagnostic value of key genes by performing immunohistochemistry (IHC) in clinical tissue samples. The compositional patterns of the infiltration of 22 immune cell types in RSA were analyzed via the CIBERSORT algorithm.ResultWe identified 403 differentially expressed genes (DEGs) and 7 DIIRGs between RSA endometrium and Non-RSA endometrium. …”
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Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review by Kapongo D. Lumamba, Gordon Wells, Delon Naicker, Threnesan Naidoo, Adrie J. C. Steyn, Mandlenkosi Gwetu

“…We categorised the computer vision platform into four technologies: image processing, object/pattern recognition, computer graphics, and deep learning. …”
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Investigating potential biomarkers associated with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis using Mendelian randomization and transcriptomic analysis by Yujia Wang, Zhimin Chen, Kaiqi Huang, Keng Ye, Shiwei He, Yanfang Xu, Hong Chen

“…Genes with a significant causal relationship were selected as candidate genes for further analysis. Machine learning algorithms, ROC curve analysis, and expression evaluation were employed to screen for biomarkers. …”
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Know your competitor! Analyzing and predicting the location of competing stores: The case study of Valora at Swiss railway stations by Thomas Wieland

“…Binary logit models are built for the formats examined in order to identify the determinants of location choice. Machine learning algorithms are used to check and optimize the predictive ability of the models. …”
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CoAt-Set: Transformed coordinated attack dataset for collaborative intrusion detection simulationMendeley Data by Aulia Arif Wardana, Grzegorz Kołaczek, Parman Sukarno

“…It is suitable for various applications, including collective threat intelligence research, analyzing distributed threat patterns, developing machine learning algorithms for distributed systems, and training simulations designed for heterogeneous network environments.…”
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Effects of urban sprawl on land use change in the peripheral villages of Tehran metropolis (case study: Tehran-Damavand axis) by ِAshkan Mohammadi, Naser Shafiei Sabet, Alireza Shakiba

“…After that, the supervised classification operation was monitored by the SVM algorithm and the detection and determination of the sprawl pattern in the study area. …”
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Development of prediction models for screening depression and anxiety using smartphone and wearable-based digital phenotyping: protocol for the Smartphone and Wearable Assessment f... by Sujin Kim, Ah Young Kim, Yu-Bin Shin, Seonmin Kim, Min-Sup Shin, Jinhwa Choi, Kyung Lyun Lee, Jisu Lee, Sangwon Byun, Heon-Jeong Lee, Chul-Hyun Cho

“…The primary outcome will be the development of machine-learning algorithms to predict depression and anxiety based on these digital biomarkers. …”
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Metabolomic Profiling Reveals Serum Tryptophan as a Potential Therapeutic Target for Systemic Lupus Erythematosus by Wang K, Zhu R, Xu M, Zhu K, Li J, Li C, Meng D, Chen H, Sun L

“…Two key metabolites, tryptophan and beta-alanine, showed significantly decreased levels in SLE patients compared to healthy controls (both p< 0.05), while exhibiting opposite patterns in other autoimmune diseases. In the mouse model, tryptophan supplementation improved renal histology, reduced proteinuria, increased naïve T cells and central memory T cells, and decreased effector T cell frequencies in both peripheral blood and spleen.Conclusion: This study demonstrates the successful application of machine learning algorithms to metabolomics data for SLE classification and identifies tryptophan and beta-alanine as potential SLE-specific biomarkers. …”
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Modeling the effects of climate change scenarios on the potential distribution of Vespa crabro Linnaeus, 1758 (Hymenoptera: Vespidae) in a Mediterranean biodiversity hotspot by Erika Bazzato, Arturo Cocco, Emanuele Salaris, Ignazio Floris, Alberto Satta, Michelina Pusceddu

“…We focused on Sardinia, a Mediterranean island with a heterogeneous morphological, geological, and climatic pattern, where V. crabro was accidentally introduced.We used 316 verified citizen science occurrences, high-resolution bioclimatic variables (40 × 40 m) specifically developed for the island, and two future climate and socio-economic scenarios for two temporal horizons (2040 and 2060) to model climatic suitability using an ensemble framework with three machine learning algorithms: Artificial Neural Networks (ANN), Generalized Boosting Model (GBM), and Random Forest (RF). …”
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Providing a Framework for Assessing and Evaluating Network Data Studies in the Fight Against Social Anomalies by Mohammad Khalili, Hamzehali Nourmohammadi, Nader Naghshineh

“…Additionally, clustering techniques, such as k-means, were employed to identify different forms of theft crimes. Classification algorithms, including neural networks, Bayesian rules, Bayesian navigation, and support vector machines, were used to predict theft crimes. …”
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Combination of Music, Artificial Intelligence, and Brainwaves for the Promotion of Mental Well-Being by Georgios Karachalios, Evina Makaroni

“…Auditory stimulation technologies—particularly those using binaural beats and other sound patterns—have already proven effective in inducing these desirable states. …”
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The Effect of Hearing Aid Amplification on Gait Parameters: A Pilot Study Using Ear-Worn Motion Sensors by Ann-Kristin Seifer, Arne Küderle, Kaja Strobel, Ronny Hannemann, Björn M. Eskofier

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Causal Discovery in Astrophysics: Unraveling Supermassive Black Hole and Galaxy Coevolution by Zehao Jin, Mario Pasquato, Benjamin L. Davis, Tristan Deleu, Yu Luo, Changhyun Cho, Pablo Lemos, Laurence Perreault-Levasseur, Yoshua Bengio, Xi Kang, Andrea Valerio Macciò, Yashar Hezaveh

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Thermal comfort and energy related occupancy behavior in Dutch residential dwellings by Anastasios Ioannou

“…Such pattern recognition algorithms can be more effective in the era of mobile internet, which allows the capturing of huge amounts of data. …”
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Artificial Intelligence for Unstructured Data Processing by Yohanes Bowo Widodo, Febrianti Widyahastuti, Mohammad Narji, Sondang Sibuea

“…By using deep learning models and advanced algorithms, AI can identify patterns and relationships in complex data, thereby providing deeper insights for better decision making. …”
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A Camera-Embedded Self-Adaptable Finger With Multi-Modal Sensing Capabilities for Robotic Manipulation by Muhammad Usman Khalid, Hafiz Muizz Ahmed Sethi, Nirmal Kumar Ravikumar, Halar Haleem, Alessandro Seitone, Mattia Frascio, Perla Maiolino, Matteo Zoppi

“…The slip detection algorithm uses a dual-threshold approach that combines the Median Absolute Deviation (MAD) and standard deviation. …”
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Deep Learning dengan Teknik Early Stopping untuk Mendeteksi Malware pada Perangkat IoT by Iwang Moeslem Andika Surya, Triawan Adi Cahyanto, Lutfi Ali Muharom

“…Although CNN was initially designed for image processing, this algorithm also effectively detects complex patterns in non-image data, such as IoT network traffic, due to its ability to extract hierarchical features. …”
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Innovative approaches in marketing for the development of the tourism industry by Yuliia Stasiuk, Andrii Kobchenko

“…For instance, AI-powered chatbots and virtual assistants provide real-time customer support, while machine learning algorithms analyze booking patterns to offer personalized travel recommendations. …”
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EXPLORING AUTOMATED SUMMARIZATION: FROM EXTRACTION TO ABSTRACTION by Svetlana G. Sorokina

“…Summaries generated by AI models offer new opportunities for analyzing machine-generated language and provide valuable data for studying how algorithms process, condense, and restructure human language.…”
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