Artificial intelligence survival models for identifying relevant risk factors for incident diabetes in Azar cohort population by Neda Gilani, Mohammadhossein Somi, Farzaneh Hamidi, Pasqualina Santaguida, Elnaz Faramarzi, Reza Arabi Belaghi

“…In contrast, the RF analysis identified 21 important variables predicting a higher probability of having diabetes. …”
Get full text

Artificial Intelligence in Revolutionizing Kidney Care and Beyond: Kid-AI Revolution by Kounaina Khan, Farhan Zameer, Pratheek Jain, Ravi KR, Vidya Niranjan, Manoj S, Ravish H, Subrahmanya Padyana

“…This review provides a comprehensive overview of AI applications in renal pathology, focusing on computer vision algorithms for kidney structure segmentation, specific pathological changes, diagnosis, treatment, and prognosis prediction based on images along with the role of machine learning (ML) and deep learning (DL) in addressing global public health issues related to various nephrological conditions. …”
Get full text

Unveiling the ageing-related genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning by Jian Huang, Lu Wang, Jiangfei Zhou, Tianming Dai, Weicong Zhu, Tianrui Wang, Hongde Wang, Yingze Zhang

“…By comparing the accuracy of the four machine learning models for disease prediction, the SVM model, which includes CEBPB, PTEN, ARPC1B, PIK3R1, and CDC42, was selected. …”
Get full text

Automated Recognition of Conidia of Nematode-Trapping Fungi Based on Improved YOLOv8 by Enming Zhao, Hongyi Zhao, Guangyu Liu, Jianbo Jiang, Fa Zhang, Jilei Zhang, Chuang Luo, Bobo Chen, Xiaoyan Yang

“…Our approach integrates an efficient channel attention (ECA) mechanism within the backbone layer of YOLOv8l, improving the algorithm’s capability to detect global information effectively. …”
Get full text

Engineering Synthetic Microbial Communities: Diversity and Applications in Soil for Plant Resilience by Arneeb Tariq, Shengzhi Guo, Fozia Farhat, Xihui Shen

“…Artificial intelligence-driven models can predict complex microbial interactions, while machine learning algorithms can analyze vast datasets to identify key microbial taxa and their functions. …”
Get full text

Replicating PET Hydrolytic Activity by Positioning Active Sites with Smaller Synthetic Protein Scaffolds by Yujing Ding, Shanshan Zhang, Xian Kong, Henry Hess, Yifei Zhang

“…Recent breakthroughs in protein structure prediction and de novo design, powered by artificial intelligence, now enable to create enzymes with desired functions without solely relying on traditional genome mining. …”
Get full text

Uniform Physics Informed Neural Network Framework for Microgrid and Its Application in Voltage Stability Analysis by Renhai Feng, Khan Wajid, Muhammad Faheem, Jiang Wang, Fazal E. Subhan, Muhammad Shoaib Bhutta

“…Moreover, its emphasis the importance of computed and estimated indices obtained through UPINN for predicting voltage collapse occurrences within the system.…”
Get full text

State of Health Estimation of Li-Ion Battery via Incremental Capacity Analysis and Internal Resistance Identification Based on Kolmogorov–Arnold Networks by Jun Peng, Xuan Zhao, Jian Ma, Dean Meng, Shuhai Jia, Kai Zhang, Chenyan Gu, Wenhao Ding

“…Three commonly used machine learning methods (BP, LSTM, TCN) and two hybrid algorithms (LSTM-KAN and TCN-KAN) were used to establish the SOH estimation model. …”
Get full text

Real-time congestion control using cascaded LSTM deep neural networks for deregulated power markets by G. Madhu Mohan, T. Anil Kumar, A. Srujana, Yasser Fouad, Alexey Mikhaylov, Nora Baranyai, Kitmo, Ch. Rami Reddy

“…Owing to their computational inefficiency, evolutionary algorithms (EAs) are ineffective for real-time congestion management, necessitating hybrid models to deliver rapid solutions. …”
Get full text

Local Diversity-Guided Weakly Supervised Fine-Grained Image Classification Method by Yuebo Meng, Xianglong Luo, Hua Zhan, Bo Wang, Shilong Su, Guanghui Liu

“…Extensive experiments conducted on four fine-grained datasets and explainable visualization demonstrate that the LDGNet can effectively enhance discriminative region localization and detailed feature acquisition for fine-grained objects, achieving competitive performance over other state-of-the-art algorithms.…”
Get full text

Scalable Semantic Adaptive Communication for Task Requirements in WSNs by Hong Yang, Xiaoqing Zhu, Jia Yang, Ji Li, Linbo Qing, Xiaohai He, Pingyu Wang

“…The experimental results show that the proposed SSAC is more robust than traditional and other semantic communication algorithms in image classification tasks, and achieves scalable compression rates without sacrificing classification performance, while improving the bandwidth utilization of the communication system.…”
Get full text

Secure Blockchain Integration Approach for Knowledge Discovery in Industrial Internet of Things by Rohan Tripathi, Ritam Rao, Vivekananda Bhat K., Abhishek Kumar Pandey, Ashok Kumar Das

Get full text

Monitoring Collaborative Interactions in Online Learning: Insights from Moodle Log Records by Anuradha Peramunugamage, Uditha Ratnayake, Shironica Karunanayaka, Ellen Francine, William Simão de Deus, Chulantha Jayawardena, Jayamali De Silva

“…The abovementioned collaborative Moodle content creation and corresponding log record analysis was executed for four modules conducted at two higher education institutions from Sri Lanka and Brazil. Regression analysis on log records and student performance on four modules indicated a positive correlation, with R2 values between 26% and 43.8%. …”
Get full text

Human-in-the-Loop Optimization of the Stiffness and Alignment of a Prosthetic Foot to Reduce the Metabolic Cost of Walking by Thijs Tankink, Han Houdijk, Johnnidel Tabucol, Marco Leopaldi, Juha M. Hijmans, Raffaella Carloni

“…Walking on the prosthetic foot with optimized settings during the post-test resulted in a significant reduction in metabolic cost compared to the pre-test with standard settings (−10.6%). …”
Get full text

ACTH-PRODUCING PERIPHERAL PULMONARY CARCINOID by I. Z. Korobkova, D. A. Dremin, S. M. Kacalov, I. V. Kirsan, A. A. Ugrimov, S. A. Zubkova, A. O. Vas’kin, T. R. Alekseeva

Get full text

Spatiotemporal evolution of 1998 extreme flood event in the Yangtze River basin from the perspective of the reconstructed GRACE/GRACE-FO data by Lilu Cui, Jiacheng Meng, Bo Zhong, Jiachun An, Yu Li, Haoyang Guo, Yuheng Lu

Get full text

Differential Diagnostic Indicators for the Appointment of Non-Steroidal Anti-Inflammatory Therapy in the Treatment of Red Eye Syndrome at the Stage of Primary Outpatient Admission.... by V. N. Trubilin, E. G. Poluninа, A. A. Kozhukhov, V. V. Kurenkov, N. V. Moreva, A. V. Trubilin, K. V. Chinenova

Get full text

REST Network: An Ensemble Deep Learning Approach for EV Charging Load Forecasting in Artificial Port Supply Chains by Elham Abdullah Alghamdi, Monagi Hassan Alkinani, Abdulwahab Ali Almazroi, Mohammed Alqarni, Eman Ali Aldhahri, Nasir Ayub

“…Traditional forecasting algorithms can fail to address logistics’ complicated, variable charge patterns and uneven data. …”
Get full text

Effect of Achieving Sustained SDAI Remission on Erosion Healing in Early Rheumatoid Arthritis - A One-year Prospective HR-pQCT Study by Qihan Wu, Ho So, Tsz-Ho Cheng, Yingzhao Jin, Sze-Lok Lau, Lai-shan Tam

“…After 12 months, a significant reduction in erosion volume and marginal osteosclerosis was observed in both groups. …”
Get full text

The Influence of Process and Slag Parameters on the Liquid Slag Layer in Continuous Casting Mold for Large Billets by Zhijun Ding, Chao Wang, Xin Wang, Pengcheng Xiao, Liguang Zhu, Shuhuan Wang

“…Increasing argon flow rate from 0.50 L·min⁻¹ to 1.00 L·min⁻¹ leads to 350 mm deeper bubble penetration, 10 mm reduction in jet penetration depth, 0.002 m·s⁻¹ increase in meniscus velocity, and decreased meniscus temperature due to bubble cooling. …”
Get full text