Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique by Karim Gasmi, Najib Ben Aoun, Najib Ben Aoun, Khalaf Alsalem, Ibtihel Ben Ltaifa, Ibrahim Alrashdi, Lassaad Ben Ammar, Manel Mrabet, Abdulaziz Shehab

“…This model enhances the feature extraction step by capturing both global and local features, thanks to the combination of different deep learning models with the ViT model. …”
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Machine Learning Models Decoding the Association Between Urinary Stone Diseases and Metabolic Urinary Profiles by Lin Ma, Yi Qiao, Runqiu Wang, Hualin Chen, Guanghua Liu, He Xiao, Ran Dai

“…<b>Background:</b> Employing advanced machine learning models, we aim to identify biomarkers for urolithiasis from 24-h metabolic urinary abnormalities and study their associations with urinary stone diseases. …”
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Research on Cross-Sensor Remote Sensing Image Super-Resolution Method Based on Diffusion Models by Ru Miao, Kai Yang, Ke Zhou, Jia Song, Shihao Fu, Cong Liu, Yuanxing Wang

“…This approach leverages the LR image as an approximation of the intermediate state in the Markov chain, reducing the number of steps required by the diffusion model and improving generation efficiency. Finally, we used RSI from the Sentinel-2 (10 m resolution) and Gaofen-2 (0.8 m resolution) sensors to validate the reconstruction performance of the diffusion model. …”
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Patient Voices in Dialysis Care: Sentiment Analysis and Topic Modeling Study of Social Media Discourse by Ravi Shankar, Qian Xu, Anjali Bundele

“…The analysis pipeline was implemented using Python’s Natural Language Toolkit, Gensim, and scikit-learn libraries, with hyperparameter tuning to maximize model performance. ResultsSentiment analysis revealed 49.2% (3711/7543) positive, 26.2% (1976/7543) negative, and 24.7% (1863/7543) neutral sentiment posts. …”
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Fuzzy-Based Fusion Model for β-Thalassemia Carriers Prediction Using Machine Learning Technique by Muhammad Ibrahim, Sagheer Abbas, Areej Fatima, Taher M. Ghazal, Muhammad Saleem, Meshal Alharbi, Fahad Mazaed Alotaibi, Muhammad Adnan Khan, Muhammad Waqas, Nouh Elmitwally

“…The proposed late fusion model performs better than previously published approaches regarding efficiency, reliability, and precision.…”
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MRCPs-and-ERS/D-Oscillations-Driven Deep Learning Models for Decoding Unimanual and Bimanual Movements by Jiarong Wang, Luzheng Bi, Aberham Genetu Feleke, Weijie Fei

“…Six-class classification accuracies of unimanual and bimanual movements achieved 80.3&#x0025;. Besides, each feature module of our model contributes to the performance. …”
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Aided Greenway Design Approach Based on Internet Big Data and AIGC Fine-Tuning Model by Yifan WU, Lu MENG, Liang LI

“…Image features are extracted using the pre-trained convolutional neural network model Inception ResNetV2 and image data is clustered by K-means clustering algorithm. …”
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A graphical modelling approach to the dissection of highly correlated transcription factor binding site profiles. by Robert Stojnic, Audrey Qiuyan Fu, Boris Adryan

“…However, existing methods do not perform well when the features (here: TF binding profiles) are highly correlated, when their association with the biological outcome is weak, and when the sample size is small. …”
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Research and Design of an Active Light Source System for UAVs Based on Light Intensity Matching Model by Rui Ming, Tao Wu, Zhiyan Zhou, Haibo Luo, Shahbaz Gul Hassan

“…In addition, to improve the robustness of the active light source system under different lighting conditions, this paper also constructs a light source color matching model based on light intensity matching. By collecting and comparing visible light images of different color light sources under various intensities and constructing the light intensity matching model using the comprehensive peak signal-to-noise ratio parameter, the model is optimized to ensure the best vision tracking performance under different lighting conditions. …”
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The HL-60 clone 15 cell line as a model for leukocyte migration–possibilities and limitations by Lena Griesbaum, Christopher Weusthof, Thorben Sauer, Timo Gemoll, Gregor Weirich, Ludger Klimek, Ludger Klimek, Julie Petry, Ali Bashiri Dezfouli, Ali Bashiri Dezfouli, Maria Shoykhet, Barbara Wollenberg

“…It is, therefore, advisable to use the cell line as an eosinophilic model only in research questions related to chemotaxis and migration.…”
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Design of an Intelligent Pear Bagging End-Effector Based on Yolov8 and SGBM Algorithm by Jing Ruijun, Liu JingKai, LiXin, ZhiguoZhao

“…The depth information accuracy obtained by the algorithm is within 3cm. The improved model, combined with SGBM, runs at 11.5 fps on the Jetson Nano embedded device, meeting real-time performance requirements.…”
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Pure data correction enhancing remote sensing image classification with a lightweight ensemble model by Huaxiang Song, Hanglu Xie, Yingying Duan, Xinyi Xie, Fang Gan, Wei Wang, Jinling Liu

“…Existing advanced methods often require substantial modifications to model architectures to achieve optimal performance, resulting in complex frameworks that are difficult to adapt. …”
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RETRACTED ARTICLE: Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson’s disease by Umesh Kumar Lilhore, Surjeet Dalal, Neetu Faujdar, Martin Margala, Prasun Chakrabarti, Tulika Chakrabarti, Sarita Simaiya, Pawan Kumar, Pugazhenthan Thangaraju, Hemasri Velmurugan

“…This research presents a hybrid model utilizing improved speech signals with dynamic feature breakdown using CNN and LSTM. …”
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Research on the Construction and Application of Earthquake Emergency Information Knowledge Graph Based on Large Language Models by Wentao Zhou, Meng Huang, Shuai Liu, Qiao You, Fanxin Meng

“…&#x201D;The method deploys a local large language model using LangChain +QWEN2.5-7B, integrates earthquake domain knowledge through LoRa fine-tuning based on earthquake experts&#x2019; classifications and industry standards, and injects seismic knowledge into the model. …”
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Novel channel attention-based filter pruning methods for low-complexity semantic segmentation models by Md. Bipul Hossain, Na Gong, Mohamed Shaban

“…This is realized by recognizing the contextual importance of the feature maps in each layer of the models and the significance of each filter to the final model performance. …”
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Construction and validation of a prognostic model based on cuproptosis-related genes in patients with multiple myeloma by KANG Zhongmin, KANG Zhongmin, LI Licheng

“…Objective‍　‍To explore the potential cuproptosis-related genes (CRGs) in patients with multiple myeloma (MM) and develop a prognostic model for improving prognosis and revealing features of the MM immune microenvironment. …”
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Intelligent irrigation strategy model for farmland using dung beetle optimization-random forest algorithms by Wenwen Hu, Yong Liu, Jun An, Shipu Xu, Zhiwen Zhou, Mingming An, Xiaokun Guo, Xiang Ma, Wenfei Jiang, Yunsheng Wang

“…The model integrates multi-source data, including time-series features, agricultural meteorological data, and irrigation management specifics, precise hyperparameter tuning could be performed via the sequence decomposition-based Dung Beetle Optimization (DBO) algorithm. …”
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A study on plant root apex morphology as a model for soft robots moving in soil. by Anand Kumar Mishra, Francesca Tramacere, Roberto Guarino, Nicola Maria Pugno, Barbara Mazzolai

“…We implemented an analytic translation of the root profile in a 3D model (CAD) to fabricate root-like probes by means of 3D printing technology. …”
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Comprehensive evaluation of machine learning models for predicting the cognitive status of Alzheimer's disease subjects and susceptible by Lucien Gnegne Meteumba, Vaghawan Prasad Ojha, Shantia Yarahmadian

“…We train more than 900 different combination of feature selector, models and hyperparameters. At last, we assess the performance of the models on multiple performance measures (accuracy, sensitivity, specificity and area under the ROC curve (AUC)). …”
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Deep learning-based automatic diagnosis of rice leaf diseases using ensemble CNN models by Prameetha Pai, S. Amutha, Seema Patil, T. Shobha, Mustafa Basthikodi, B. M. Ahamed Shafeeq, Ananth Prabhu Gurpur

“…These models were selected based on diverse architectural principles to ensure complementary feature extraction capabilities. …”
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