Early prediction of CKD from time series data using adaptive PSO optimized echo state networks by Thangadurai Anbazhagan, Balamurugan Rangaswamy

“…Presently, existing methods that effectively detect CKD cannot detect symptoms early on. This problem motivates researchers to work on a predictive model that successfully detects disease symptoms in the early stages. …”
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Field programmable silicon microring WDM transceiver leveraging monolithically integrated phase-change materials by Xing Yang, Shihuan Ran, Ziquan Li, Liangjun Lu, Yu Li, Ngon Phu Wai, MingHua Zhang, Guo-Qiang Lo, Jianping Chen, Linjie Zhou

“…These advancements position Sb2Se3-integrated MRRs as a promising solution for large-scale, energy-efficient photonic transceivers in next-generation optical communication systems.…”
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3D-SCUMamba: An Abdominal Tumor Segmentation Model by Juwita, Ghulam Mubashar Hassan, Amitava Datta

“…The proposed model efficiently models global dependencies while maintaining stable training dynamics and efficient inference. …”
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A deep neural network model with spectral correlation function for electrocardiogram classification and diagnosis of atrial fibrillation by Sara Mihandoost

“…The obtained results demonstrate that the proposed approach efficiently represents ECG signals through SCF coefficients, leading to the accurate detection of AF with an average accuracy of 92.76% and an average F1-score of 89.1%.…”
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Recent advancements in nanomaterial-based biosensors for diagnosis of breast cancer: a comprehensive review by Yalda Yazdani, Fereshtehsadat Jalali, Habib Tahmasbi, Mitra Akbari, Neda Talebi, Seyed Abbas Shahrtash, Ahmad Mobed, Mahsa Alem, Farhood Ghazi, Mehdi Dadashpour

“…However, these methods are limited by cost, analysis time, and complexity. Therefore, it is necessary to develop an ultrasensitive, fast, low-cost, simple method for BRCA1 detection. …”
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Insights and Recommendations for the Assessment and Design of Fault Diagnosis Methods Applied to Modern Distribution Systems by Talita M. O. A. Cunha, Gabriela N. Lopes, Leonardo S. Lessa, Moises J. B. B. Davi, Mario Oleskovicz, Jose C. M. Vieira

“…The growing integration of Distributed Generation (DG) and the complexity of modern distribution networks present new challenges in fault diagnosis. …”
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Features of organizational and technological solutions for the construction and installation of large-span buildings by Tatyana K. Kuzmina, Anton N. Bolshakov, Nadezhda A. Lukyanova, Anastasija V. Puzikova

“…These structures allow to create complex architectural solutions, creating lightweight, aesthetically attractive cover ings. …”
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World Café approach: exploring the future vision of oral anticoagulants for patients with atrial fibrillation (AF) in Ireland by Colin Bradley, Stephen McCarthy, Aileen Murphy, Stephen Brosnan, Paidi O’Raghallaigh, Ann Kirby

“…While consensus for developing evidence-based pathways to maximise efficiency and effectiveness of AF treatment was evident, it would require a shared vision between stakeholders of integrated care. …”
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A quantum machine learning framework for predicting drug sensitivity in multiple myeloma using proteomic data by M. Priyadharshini, B. Deevena Raju, A. Faritha Banu, P. Jagdish Kumar, V. Murugesh, Oleg Rybin

“…QSVM employs quantum kernels to map data into a higher-dimensional Hilbert space, so that the model can detect complex patterns in MM drug resistance. qPCA reduces dimensionality without loss of important variance, and thus improves computation efficiency. …”
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Autonomous Vehicle Security: Hybrid Threat Modeling Approach by Amal Yousseef, Yu-Zheng Lin, Shalaka Satam, Banafsheh Saber Latibari, Jesus Pacheco, Soheil Salehi, Salim Hariri, Pratik Satam

“…Autonomous vehicles (AVs) are poised to revolutionize modern transportation, offering enhanced safety, efficiency, and convenience. However, AV architectures' increasing connectivity and complexity have introduced significant cybersecurity risks. …”
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Automated Models for Predicting Software Defects in Hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) Parallel Programs Using Deep Learning by Amani Saad Althiban, Hajar M. Alharbi, Lama A. Al Khuzayem, Fathy Elbouraey Eassa

“…Hybrid Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) parallel programs are pivotal for scalability and efficiency in high-performance computing (HPC), especially as systems approach exa-scale operations. …”
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EG-VAN: A Global and Local Attention-Based Dual-Branch Ensemble Network With Advanced Color Balancing for Multi-Class Skin Cancer Recognition by Adnan Saeed, Khurram Shehzad, Saim Ahmed, Ahmad Taher Azar

“…Despite their sophistication, existing methods struggle to generalize well across diverse cases, and their computational complexity often limits real-world applicability. To address these challenges, we introduce a novel dual-path architecture in the Efficient Global-Vision Attention-Net (EG-VAN) for early detection of skin cancer. …”
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Token Mixing for Breast Cancer Diagnosis: Pre-Trained MLP-Mixer Models on Mammograms by Hosameldin O. A. Ahmed, Asoke K. Nandi

“…Breast cancer remains a leading cause of mortality among women, necessitating accurate and computationally efficient diagnostic solutions. Deep learning, particularly convolutional neural networks (CNNs), has significantly advanced mammographic analysis by automating feature extraction and improving early detection. …”
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A growth posture identification method of immature peaches in natural environments by Jidong Lv, Liangliang Niu, Ying Han, Xiaoqin Sun, Lingyun Wang, Hailong Rong, Ling Zou

“…The network models employed in single detection algorithms exhibit complexity and pose challenges for deployment on mobile terminals as they heavily rely on the availability of labeled samples. …”
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Simultaneous Speech and Eating Behavior Recognition Using Data Augmentation and Two-Stage Fine-Tuning by Toshihiro Tsukagoshi, Masafumi Nishida, Masafumi Nishimura

“…The experimental evaluations demonstrate that the proposed method maintains speech recognition accuracy while achieving high detection performance for eating behaviors, with an F1 score of 0.918 for chewing detection and 0.926 for swallowing detection. …”
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A Differential Approach to Choosing Extracorporeal Detoxification Methods for Abdominal Sepsis by L. Ye Shukevich, Yu. A. Churlyaev, Ye. V. Grigoryev, D. L. Shukevich, K. N. Kondyukov, A. S. Razumov

“…A differential approach to choosing the methods of extracorporeal detoxification in the complex treatment of abdominal sepsis in the context of endogenous intoxication in order to enhance the efficiency of medical measures was pathogeneti-cally substantiated. …”
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Eco-friendly HPTLC method for Trifluridine and Tipiracil determination: Quality-by-design meets green analytical chemistry by Amruta Balekundri, Eknath D. Ahire, Rakesh U. Shelke, Dinesh D. Rishipathak, Sanjay J. Kshirsagar

“…Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, necessitating efficient treatment strategies and accurate analytical methods. …”
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The effect of dietary transition on infant microbiota composition and metabolic activity captured with the simulator of the human intestinal microbial ecosystem (SHIME) by Shadi Pakroo, Samira Soltani, Armin Tarrah, Gisèle LaPointe

“…A reduction in butyrate concentration following the transition to adult feed may reflect a temporary shift in microbial metabolic activity rather than a long-term impact on energy extraction efficiency in vivo.…”
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Single-Phase Bridgeless Three-Level Power Factor Correction Topologies Based on the Embedded Construction Scheme by Tianyue Wang, Hui Ma, Wenjing Li, Guixi Miao, Qingsong Zhao, Meng Si, Yun Lu

“…The circuit can work in the PFC mode under the rated working conditions and reflects the characteristics of three levels. The circuit can respond quickly and work normally under a variety of complex working conditions and can work in a diode rectification mode when the driving voltage signal is lost. …”
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AI-driven healthcare innovations for enhancing clinical services during mass gatherings (Hajj): task force insights and future directions by Ala’a Alquayt, Ohoud Aljuhani, Abdullah F. Alharthi, Rahaf Alqahtani, Anas Khan, Ahmed Al-jedai, Abdulqader Almoeen, Mohammed Alshennawi, Hisham A. Badreldin, Abdulrhman Aljouie, Lubna A. Alnasser, Abdulmajeed M. Alshehri, Mohammed Y. Alzahrani, Haifa A. Alhaidal, Raghad Alhajaji, Salman Alotaibi, Esraa Z. Redhwan, Fahad Alharthi, Badr G. Alghamdi, Khalid Al Sulaiman

“…Abstract Background Due to the high complexity of healthcare during mass gatherings (MG), the integration of Artificial Intelligence (AI) might be crucial. …”
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