Development of a clinical decision support system for breast cancer detection using ensemble deep learning by Jasjeet Kaur Sandhu, Chetna Sharma, Amandeep Kaur, Saroj Kumar Pandey, Anurag Sinha, J. Shreyas

“…The team improves its capacity to extricate intricate patterns and features from medical imaging data by incorporating the Kelm Extreme Learning Machine (KELM), Deep Belief Network (DBN), and other DL architectures. …”
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Estimating pedestrian traffic with Bluetooth sensor technology by Avital Angel, Achituv Cohen, Sagi Dalyot, Pnina Plaut

“…One of the main problems is detecting pedestrians from Bluetooth records since their behavior and movement patterns share similarities with other urban transportation modes. …”
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Optimization of CNN Activation Functions using Xception for South Sulawesi Batik Classification by Aswan Aswan, Eva Yulia Puspaningrum, Billy Eden William Asrul

“…The results demonstrate that selecting an optimal activation function substantially enhances convolutional neural network classification of complex batik patterns. …”
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Biologically inspired hybrid model for Alzheimer’s disease classification using structural MRI in the ADNI dataset by Houmem Slimi, Imen Cherif, Sabeur Abid, Mounir Sayadi

“…This study proposes a hybrid convolutional neural network-spiking neural network (CNN-SNN) architecture to classify AD stages using structural MRI (sMRI) data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). …”
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FFT-RDNet: A Time–Frequency-Domain-Based Intrusion Detection Model for IoT Security by Bingjie Xiang, Renguang Zheng, Kunsan Zhang, Chaopeng Li, Jiachun Zheng

“…These time–frequency domain features are fused to construct a two-dimensional feature space, which is then processed by a streamlined residual network using depthwise separable convolution. This network effectively captures complex periodic attack patterns with minimal computational overhead. …”
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Study on the interaction characteristics between pot seedling and planter based on hanging cup transplanter by Hongbin Bai, Fandi Zeng, Qiang Su, Ji Cui, Xuying Li

“…The accuracy of the simulation model was validated using the substrate loss rate after planting as an evaluation metric. Furthermore, based on Artificial Neural Network technology and incorporating BP and GA-BP algorithms, a nonlinear model of the interaction between pot seedlings and the planting device under various parameter conditions was established using simulated field planting test results as the dataset. …”
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Evolving Spiking Neural Network Model for PM2.5 Hourly Concentration Prediction Based on Seasonal Differences: A Case Study on Data from Beijing and Shanghai by Hengyuan Liu, Guibin Lu, Yangjun Wang, Nikola Kasabov

“…Furthermore, inadequate processing of the available spatio-temporal data has precluded the capture of predictive historical patterns. Therefore, we have developed a staging evolving spiking neural network (eSNN) model named Staging-eSNN that first employs a time series clustering algorithm to distinguish the seasonal from the diurnal variation in the PM2.5 concentration. …”
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A Multi-Dimensional Evaluation of Street Vitality in a Historic Neighborhood Using Multi-Source Geo-Data: A Case Study of Shuitingmen, Quzhou by Guoquan Zheng, Lingli Ding, Jiehui Zheng

“…This study takes the Shuitingmen Historical and Cultural Neighborhood in Quzhou, China, as a case study and develops a multi-dimensional vitality evaluation framework incorporating point-of-interest (POI) data, location-based service (LBS) heatmaps, street network data, historical resources, and environmental perception indicators. …”
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IFP35, a novel DAMP, aggravates neuroinflammation following acute ischemic stroke via TLR4/NF-κB/NLRP3 signaling by Mengmeng Zhang, Bingnan Guo, Xiaowei Zhang, Dong Han, Lanxin Lv, Xiaoqing Yan, Chenglei Su, Dafei Chai, Ningjun Zhao, Xianliang Yan, Shuqun Hu

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Optimized Motion Capture for Cricket Shot Classification Using Minimal Hardware and Machine Learning by J. Ishan Randika, Kanishka Rajamanthri, Avishka Kothalawala, Niroshan Gunawardana, Ashan Induranga, Pathum Weerakkody, Kaveendra Maduwantha, B. T. G. S. Kumara, Kaveenga Koswattage

“…Motion data collected from the system was analyzed to extract distinct angle variation patterns associated with different batting shots. These patterns were used to train a hybrid machine learning model combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. …”
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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…Observational and qualitative studies evaluating AI in the analysis of breastfeeding patterns and human milk composition have been conducted. …”
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Parking search identification in vehicle GPS traces by Siavash Saki, Tobias Hagen

“…Utilizing this unique dataset, we developed a deep learning neural network model that accurately identifies parking search routes in GPS data and predicts search duration. …”
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A novel approach to intrusion detection system using hybrid flower pollination and cheetah optimization algorithm by Deepshikha Kumari, Prashant Pranav, Abhinav Sinha, Sandip Dutta

“…Key performance metrics were analysed to assess the model’s effectiveness in detecting malicious activities in complex network traffic patterns. The hybrid model demonstrated superior performance compared to existing IDS approaches. …”
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Botnet detection in internet of things using stacked ensemble learning model by Mudasir Ali, Muhammad Faheem Mushtaq, Urooj Akram, Daniel Gavilanes Aray, Manuel Masias Vergara, Hanen Karamti, Imran Ashraf

“…The UNSW-NB15 dataset is used to train machine learning models and evaluate their effectiveness in detecting cyber-attacks on IoT networks. …”
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Prediction of microbe-drug associations using a CNN-Bernoulli random forest model by Zihao Song, Qingnuo Li, Jincheng Zhao, Qinggang Bu, Zekang Bian, Jia Qu

“…A convolutional neural network (CNN) is then used to reduce the dimensionality of all feature vectors, including those in the training set. …”
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Exploring the relationship between sepsis and Golgi apparatus dysfunction: bioinformatics insights and diagnostic marker discovery by Wanli Ma, Xinyi Liu, Ran Yu, Jiannan Song, Lina Hou, Ying Guo, Hongwei Wu, Dandan Feng, Qi Zhou, Haibo Li

“…To further evaluate immune microenvironmental features, unsupervised clustering was applied to identify immunological subgroups. …”
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A Coupled Coordination and Network-Based Framework for Optimizing Green Stormwater Infrastructure Deployment: A Case Study in the Guangdong–Hong Kong–Macao Greater Bay Area by Jiayu Zhao, Yichun Chen, Rana Muhammad Adnan Ikram, Haoyu Xu, Soon Keat Tan, Mo Wang

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Comparative Efficacy and Safety of Potassium-Competitive Acid Blocker– and Proton Pump Inhibitor–Based Bismuth Quadruple Therapy for Helicobacter pylori Eradication: A Network Meta... by Iqbal Taufiqqurrachman, Ari Fahrial Syam, Hasan Maulahela, Murdani Abdullah, Muhammad Miftahussurur, Yoshio Yamaoka

“…Therefore, tailored therapies based on local resistance patterns remain critical considerations in clinical practice.…”
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Prevalence of infection and associated factors after intramedullary nailing in African countries with the Surgical Implant Generation Network program: A systematic review and meta-... by Destaw Endeshaw, Natnael Kebede, Abiyu Abadi Tareke, Ousman Adal, Eyob Getachew, Asnake Gashaw Belayneh, Getnet Alemu Andargie, Kedir Seid, Gebeyehu Lakew, Amlaku Nigusie Yirsaw, Mitiku Tefera, Eyob Ketema Bogale, Tadele Fentabel Anagaw, Eneyew Talie Fenta

“…Objective: To assess the prevalence of infection and associated factors after Surgical Implant Generation Network nailing in African countries with the Surgical Implant Generation Network program. …”
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De Novo Design of Large Polypeptides Using a Lightweight Diffusion Model Integrating LSTM and Attention Mechanism Under Per-Residue Secondary Structure Constraints by Sisheng Liao, Gang Xu, Li Jin, Jianpeng Ma

“…By integrating a lightweight LSTM-attention neural network as the denoiser within a diffusion framework, PPD offers an innovative and efficient approach to polypeptide generation. …”
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