USE OF ARTIFICIAL INTELLIGENCE TO IDENTIFY AND CORRECT MISCONCEPTIONS ABOUT RADIATION by Oleksandr Tymoshchuk

“…AI tools, including natural language processing models for text analysis and machine learning algorithms for misconceptions classification, were used to provide personalised feedback and targeted corrective information. …”
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Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson’s Disease Using Vocal Characteristics: A Comparative Analysis by Mehmet Meral, Ferdi Ozbilgin, Fatih Durmus

“…This study seeks to assess the effectiveness of machine learning algorithms optimized to classify PD based on vocal characteristics to serve as a non-invasive and easily accessible diagnostic tool. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Advances in artificial intelligence (AI) address these challenges through predictive modeling and personalized medicine approaches. Machine learning models trained on extensive molecular datasets predict skin permeability and accelerate the selection of suitable drug candidates. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…A lack of more extensive and consistent datasets was the most common issue, followed by the need to improve existing models.…”
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Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Particular attention is paid to data-driven methods, including probabilistic models such as Hidden Markov Models (HMMs), classical machine learning algorithms such as Support Vector Machines (SVMs) and K-Nearest Neighbors (KNN), and deep learning architectures such as Convolutional Neural Networks (CNNs), all of which have demonstrated high accuracy in both laboratory and real-world settings. …”
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A Novel Bilateral Data Fusion Approach for EMG-Driven Deep Learning in Post-Stroke Paretic Gesture Recognition by Alexey Anastasiev, Hideki Kadone, Aiki Marushima, Hiroki Watanabe, Alexander Zaboronok, Shinya Watanabe, Akira Matsumura, Kenji Suzuki, Yuji Matsumaru, Hiroyuki Nishiyama, Eiichi Ishikawa

“…This approach significantly enhanced model performance across both datasets, as evidenced by improvements in sensitivity, specificity, accuracy, and F1-score metrics. …”
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Use of artificial intelligence in the diagnosis, treatment and surveillance of patients with kidney cancer by E. Yu. Timofeeva, С. R. Azilgareeva, A. O. Morozov, M. S. Taratkin, D. V. Enikeev

“…AI model algorithms may be used to identify patients at high risk of relapse requiring long-term follow-up, as well as to develop individual treatment and follow-up strategies. …”
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Predicting outcomes following endovascular aortoiliac revascularization using machine learning by Ben Li, Badr Aljabri, Derek Beaton, Leen Al-Omran, Mohamad A. Hussain, Douglas S. Lee, Duminda N. Wijeysundera, Ori D. Rotstein, Charles de Mestral, Muhammad Mamdani, Mohammed Al-Omran

“…We developed machine learning algorithms that predict 30-day post-procedural outcomes. …”
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Lightweight Multiscale Spatio-Temporal Graph Convolutional Network for Skeleton-Based Action Recognition by Zhiyun Zheng, Qilong Yuan, Huaizhu Zhang, Yizhou Wang, Junfeng Wang

“…However, it is challenging for current models to handle distant dependencies that commonly exist between human skeleton nodes, which hinders the development of algorithms in related fields. …”
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Modifiable Factors and 10‐Year and Lifetime Risk of Cardiovascular Disease in Adults With New‐Onset Diabetes: The Kailuan Cohort Study by Shouling Wu, Yuntao Wu, Yi Ning, Xiang Peng, Haiyan Zhao, Jun Feng, Liming Lin, Chunyu Ruan, Shuohua Chen, Jinwei Tian, Cheng Jin

“…Ten‐year and lifetime (ages 25–85) CVD risks were estimated using Fine–Gray competing risks models. Results During a median follow‐up of 7.6 years, 1371 participants experienced CVD events. …”
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Enhancing Port Energy Autonomy Through Hybrid Renewables and Optimized Energy Storage Management by Dimitrios Cholidis, Nikolaos Sifakis, Nikolaos Savvakis, George Tsinarakis, Avraam Kartalidis, George Arampatzis

“…By bridging the gap between theoretical modeling and practical implementation, it offers a scalable and adaptable solution for improving cost efficiency and energy resilience in port operations.…”
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Bidirectional Relationship Between Hypoalbuminemia and Postoperative Pneumonia in Elderly Hip Fracture Patients: A Retrospective Cohort Study by Wang J, Yu H, Xu X, Guo J

“…After predefined participants selection inclusion and exclusion criteria, 1661 surgically treated HF patients were included and analyzed utilizing multiple statistical models, including univariate logistic regression, Lasso regression, and Boruta algorithm for variable selection, while multivariate logistic regression and propensity score matching (PSM) for assess the bidirectional relationship between hypoalbuminemia and postoperative pneumonia. …”
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Integrating artificial Intelligence-Based metaheuristic optimization with Machine learning to enhance Nanomaterial-Containing latent heat thermal energy storage systems by Ali Basem, Hanaa Kadhim Abdulaali, As’ad Alizadeh, Pradeep Kumar Singh, Komal Parashar, Ali E. Anqi, Husam Rajab, Pancham Cajla, H. Maleki

“…The proposed strategy combines machine learning algorithms, including multilayer perceptron neural network (MLPNN), generalized additive model (GAM), Gaussian kernel regression (GKR), support vector machine (SVM), and Gaussian process regression (GPR) with artificial intelligence-based metaheuristic optimization algorithms (PSO and GA) to optimize their structural/training parameters. …”
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The impact of artificial intelligence on medical diagnostics: A letter to the editor by Sahar Imtiaz, Sheikh Abdul Qadir Jillani

“… Madam, Artificial intelligence (AI) describes the generation of intelligent machines that are capable of carrying out activities that usually call for human intellect. (1) It involves creating algorithms and models that enable computers to learn from and analyze vast amounts of data, recognize patterns, make decisions, and even engage in natural language processing…”
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An Intelligent LoRaWAN-Based IoT Device for Monitoring and Control Solutions in Smart Farming Through Anomaly Detection Integrated With Unsupervised Machine Learning by Maram Fahaad Almufareh, Mamoona Humayun, Zulfiqar Ahmad, Asfandyar Khan

“…Predominantly, the study also indicates precision in the temperature variation prediction model through the use of the predictive model based on the linear regression and random forest algorithms. …”
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YOLO-SAIL: Attention-Enhanced YOLOv5 With Optimized Bi-FPN for Ship Target Detection in SAR Images by Prabu Selvam, P. Shanmuga Sundari, M. Tamilselvi, T. Suresh, M. Murugappan, Muhammad E. H. Chowdhury

“…As a solution to these challenges, this research article introduces a new ship identification model known as YOLO-SAIL. The improved Bi-directional Feature Pyramid Network (Bi-FPN) has been replaced by a conventional Path Aggregation Network (PAN) to extract more powerful semantic features and sharpen the distinction between multi-scale targets. …”
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Machine learning-driven SLC prognostic signature for glioma: predicting survival and immunotherapy response by Jianghua Lin, Xiao Yang, Kaijun Zhao, Yu’e Liu, Yu’e Liu

“…Identifying novel molecular biomarkers is essential for improving prognosis and developing more effective therapies.MethodsIn this study, we developed a solute carrier family prognostic signature (SLCFPS) for gliomas using univariate Cox regression and machine learning algorithms across five independent glioma cohorts. …”
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Reinforcement learning for an efficient and effective malware investigation during cyber incident response by Dipo Dunsin, Mohamed Chahine Ghanem, Karim Ouazzane, Vassil Vassilev

“…Future work will incorporate more advanced RL algorithms and large language models (LLMs) to further enhance the effectiveness of malware forensic analysis.…”
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Lightweight and robust ship detection method driven by self-attention mechanism by Feng MA, Zihui SHI, Jie SUN, Chen CHEN, Xianbin MAO, Xinping YAN

“…Subsequently, considering the uneven distribution and minor scale variations of ship targets in the dataset, two detection layers are retained to reduce model parameters and further enhance model performance. …”
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A novel ensemble of hybrid starling murmuration optimized stacked gated Ghostnets for robust classification of DDoS attacks by P. Mamatha, S. Balaji, S. Sai Anuraghav

“…Multiple heterogeneous datasets related to the DOS attacks are utilised to analyse the proposed model utilising the metrics including precision, accuracy, specificity, F1-score and recall. …”
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