A Comprehensive Machine Learning Approach for COVID-19 Target Discovery in the Small-Molecule Metabolome by Md. Shaheenur Islam Sumon, Md Sakib Abrar Hossain, Haya Al-Sulaiti, Hadi M. Yassine, Muhammad E. H. Chowdhury

“…Key techniques such as feature ranking, standard scaling, and SMOTE were used to address class imbalances, thus enhancing model robustness. …”
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Intervention of machine learning in bladder cancer research using multi-omics datasets: systematic review on biomarker identification by Blessy Kiruba, P. S. Athul Narayan, Badhari Raj, S. Rohieth Raj, Sam George Mathew, Sudhakaran Sajitha Lulu, Vino Sundararajan

“…Recent research has heavily focused on multi-omics analysis, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics, for biomarker identification. …”
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DVF-NET: Bi-Temporal Remote Sensing Image Registration Network Based on Displacement Vector Field Fusion by Mingliang Xue, Yiming Zhang, Shucai Jia, Chong Cao, Lin Feng, Wanquan Liu

“…A key innovation of this method is the incorporation of a Structural Attention Module (SAT), which enhances the model’s ability to focus on structural features, improving the feature extraction process. …”
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From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications by Evgenia Gkintoni, Anthimos Aroutzidis, Hera Antonopoulou, Constantinos Halkiopoulos

“…Key signal processing techniques used during this process include spectral features, connectivity analysis, and frontal asymmetry detection, which helped enhance the performance of recognition. …”
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Early Diagnosis of Alzheimer’s Disease Using Adaptive Neuro K-Means Clustering Technique by Karan Kumar, Shweta Agrawal, Isha Suwalka, Celestine Iwendi, Cresantus N. Biamba

“…The approach integrates the Adaptive Moving Self-Organizing Map (AMSOM), a neural network technique for unsupervised training and tissue segmentation, with K-means clustering and Principal Component Analysis (PCA) for feature selection. AMSOM dynamically updates neuron weights to improve segmentation accuracy. …”
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Intriguing Nature of AM Her–type Candidate CXOU J204734.8+300105 by Rahul Sharma, Chetana Jain, Biswajit Paul, Anjan Dutta, Vikram Rana

“…The detection and characterization of periodic X-ray signals are crucial for identifying new compact objects and studying the mechanisms powering their emission. …”
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IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition by Mashael Maashi, Huda G. Iskandar, Mohammed Rizwanullah

“…Furthermore, the improved MobileNetV3 model is employed for the feature extraction process. Moreover, the convolutional neural network with a bidirectional gated recurrent unit and attention (CNN-BiGRU-A) model classifier is implemented for the SLR process. …”
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Optical and SAR Image Registration in Equatorial Cloudy Regions Guided by Automatically Point-Prompted Cloud Masks by Yifan Liao, Shuo Li, Mingyang Gao, Shizhong Li, Wei Qin, Qiang Xiong, Cong Lin, Qi Chen, Pengjie Tao

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AI in Endoscopic Gastrointestinal Diagnosis: A Systematic Review of Deep Learning and Machine Learning Techniques by Jovita Relasha Lewis, Sameena Pathan, Preetham Kumar, Cifha Crecil Dias

“…It provides a detailed analysis of Machine learning (ML) techniques like preprocessing, segmentation, feature extraction, and classification. …”
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Evaluation of groundwater storage variability and relationship with hydrometeorological factors in the Huang-Huai-Hai Plain, China, using GRACE and GLDAS Data (2002–2023) by Fengmin Hu, Bingjie Liang, Gao Yang, Zhong Lu, Zhanshi Li, Yu Fu

“…Partial correlation analysis indicated that evapotranspiration and surface runoff negatively correlated with GWSA, while precipitation and temperature positively correlated. …”
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A novel approach in diagnosing knee osteoarthritis for content based image retrieval in big data analytics and medical images by Pinar Gundogan Bozdag, Hurşit Burak Mutlu, Mucahit Karaduman, Muhammed Yildirim, M. Attique Khan, Shrooq Alsenan, Jamel Baili, Yunyoung Nam

“…In this study, CBIR techniques were preferred to detect knee osteoarthritis. In the proposed method, feature extraction was performed using DarkNet53, Histogram of Oriented Gradients (HOG), and Local Binary Patterns (LBP). …”
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Machine learning-based prediction of diabetic peripheral neuropathy: model development and clinical validation by Meng Sun, Xingling Sun, Fei Wang, Li Liu

“…Shapley Additive Explanations (SHAP) analysis provided interpretability, highlighting the clinical importance of diabetes duration and HbA1c among other predictors.ConclusionThis study establishes a robust predictive tool for early DPN detection, laying the foundation for improved prevention and management strategies.…”
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Research on Interval Probability Prediction and Optimization of Vegetation Productivity in Hetao Irrigation District Based on Improved TCLA Model by Jie Ren, Delong Tian, Hexiang Zheng, Guoshuai Wang, Zekun Li

“…This model employs TTHHO to effectively navigate the search space and adaptively optimize network node positions, integrates CNN-LSSVM for feature extraction and regression analysis, and incorporates ABKDE for probability density function estimation and outlier detection, resulting in accurate interval probability prediction and enhanced model resilience to interference. …”
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An Attention-based Model for Recognition of Facial Expressions Using CNN-BiLSTM by Sushil Kumar Singh, Manish Kumar, Ikram Majeed Khan, A. Jayanthiladevi, Chirag Agarwal

“…To address the challenges posed by non-frontal visual features, this study proposes a hybrid model that fusion of Convolutional Neural Networks (CNN) and Bidirectional Long Short-Term Memory (BiLSTM), augmented with a point multiplication attention model and Linear Discriminant Analysis (LDA). …”
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Research on fault localization method of valve area in converter station based on metric learning and knowledge reasoning by WEI Yun, LI Xianwei, ZHANG Yanlong, CAO Hui, XU Dan, QIU Junhong

“…A triplet of electrical quantity-switch quantity-fault type is formed, which stores fault location knowledge in the form of a knowledge graph, and designs a knowledge graph inference algorithm to achieve fault location based on waveform data analysis. The experimental results show that the proposed method achieves a fault location detection rate of over 92% based on the recorded waveform data of the converter station valve area, which will effectively improve the efficiency of fault location for operators.…”
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Anytime Optimal Trajectory Repairing for Autonomous Vehicles by Kailin Tong, Martin Steinberger, Martin Horn, Selim Solmaz, Daniel Watzenig

“…A statistical analysis of 100 scenarios demonstrates that our trajectory-repairing framework outperforms the path-speed decoupled repairing framework in terms of scenario success rate. …”
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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…Conversely, high‐frequency features related to charge transfer resistance play a dominant role in the KP detection. …”
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A CGAN-based adversarial attack method for data-driven state estimation by Qi Wang, Jing Zhang, Jianxiong Hu, Shutan Wu, Shiyi Hou, Yi Tang

“…Comparative analysis with other traditional adversarial attack methods further indicates its effectiveness, thereby uncovering critical security vulnerabilities in data-driven state estimation algorithms.…”
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Searching for Internal Absorption Signatures in High-redshift Blazars by A. Dmytriiev, A. Acharyya, M. Böttcher

“…For the remaining, higher-redshift sources, the limited photon statistics prevent a reliable detection of internal opacity features.…”
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XABH-CNN-GRU: Explainable attention-based hybrid CNN-GRU model for accurate identification of common arrhythmias by Abduljabbar S. Ba Mahel, Fahad Mushabbab G. Alotaibi, Zenebe Markos Lonseko, Ni-Ni Rao

“…This model is designed to capitalize on the unique features of arrhythmic patterns and enhance classification metrics. …”
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