Melanoma Skin Lesion Classification Using Neural Networks: A systematic review by ahmed hammo, Mohammed Younis

“…Finally, a research agenda was highlighted to advance the field towards the new trends.…”
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DBANet: a dual-branch convolutional neural network with attention enhancement for motor imagery classification by Dandan Liang, Brendan Z. Allison, Ruiyu Zhao, Andrzej Cichocki, Jing Jin

“…Finally, the combined features are applied for classification.Results The subject-dependent results of our proposed framework on the three datasets (BCI Competition IV dataset 2b, 2a and ECUST dataset) are 85.19%, 85.15% and 75.24%, respectively.Comparison with existing methods We conduct an extensive study between the proposed framework and five State-of-the-Art models, including FBCSP, ShallowConvNet, EEGNet, FBCNet, and IFNet.Conclusions for research articles We certificate the superiority of the proposed framework by conducting comparative experiments on three datasets with advanced MI decoding algorithms.…”
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METHODOLOGICAL APPROACH TO CONSTRUCTION OF A SYSTEM FOR DETECTION AND PREVENTION OF DESTRUCTION OF THE ACTIVITIES OF CONSTRUCTION PARTICIPANTS by Mykhailo Malykhin, Denys Dubinin, Olha Bielienkova

“…The methodological foundation of the research combines system analysis, risk-oriented modelling, and process mapping techniques. …”
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Analysis of the main approaches to modeling management processes for special-purpose organizational and technical systems by A. F. Salnikov, K. V. Ivanova, N. A. Merkulova

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A beginner’s approach to deep learning applied to VS and MD techniques by Stijn D’Hondt, José Oramas, Hans De Winter

“…This review is aimed at computational chemists with knowledge of molecular modelling, who wish to possibly integrate DL approaches in their research and already have a basic understanding of the fundamentals of DL. …”
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Assessing the Effects of Climate Change and Land‐Use Changes on Extreme Discharge in the Western Watershed of Lake Urmia, Iran by Ghasem Farahmand, Behzad Hessari, Hossein Salehi

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Backfire Effect Reveals Early Controversy in Online Media by Songtao Peng, Tao Jin, Kailun Zhu, Qi Xuan, Yong Min

“…Therefore, controversy detection becomes important for computational and social sciences. Previous research on detection methods has primarily focused on larger datasets and more complex computational models but has rarely examined the underlying mechanisms of conflict, particularly the psychological motivations behind them. …”
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Assessment of the applicability of multi-satellite precipitation products on the Loess Plateau over the past four decades by Rui Liu, Liu Yang, Zhengguo Shi, Mengdao Xing

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SLAM: Sales Lead AMplification Through GenAI and ML for e-Learning Platforms by Ganesan Ramachandran, Tanmay Narang, Vallidevi Krishnamurthy

“…This study investigates sales lead prediction utilizing machine learning techniques, with a particular focus on the ensemble method of stacking algorithms. The research objective is to improve the predictive accuracy of sales lead identification through the utilization of advanced machine learning methodologies. …”
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Predicting adherence to gamified cognitive training using early phase game performance data: Towards a just-in-time adherence promotion strategy. by Yuanying Pang, Ankita Singh, Shayok Chakraborty, Neil Charness, Walter R Boot, Zhe He

“…We aimed to: (1) identify the cognitive games with the strongest adherence prediction and their key performance indicators; (2) compare baseline characteristics and game performance indicators for adherence prediction, and (3) test ensemble models that use baseline characteristics and game performance data to predict adherence over ten weeks.<h4>Research design and method</h4>Using machine learning algorithms including logistic regression, ridge regression, support vector machines, classification trees, and random forests, we predicted adherence from weeks 3 to 12. …”
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Management of a Patient with Severe Hypotension and Advanced Heart Failure with Reduced Left Ventricular Ejection Fraction by M. S. Bychkova, E. V. Reznik

“…It is difficult to select and titrate the drugs recommended for treatment of heart failure, so that the prescribed therapy compensates the patient and does not cause the development of side effects. Step–by–step algorithms for prescribing and correcting drug therapy for heart failure patients with hypotension have been developed. …”
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Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

“…This study provides actionable insights for stakeholders and recommends future research exploring strategies for overcoming adoption challenges, fostering technological innovation, and capacity building in Saudi Arabia’s construction sector.…”
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Comparing the effect of pre-anesthesia clonidine and tranexamic acid on intraoperative bleeding volume in rhinoplasty: a machine learning approach by Zahra Asghari Varzaneh, Akram Hemmatipour, Hadi Kazemi-Arpanahi

“…The results revealed that the Linear and Ridge regression algorithms outperformed all other models based on three evaluation metrics: mean absolute error (MAE), mean square error (MSE), and R-squared. …”
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DATA COMPRESSION USING WAVELET TRANSFORM IN BIOTELEMETRY SYSTEMS by O.E. Bezborodova, A.Yu. Bodin, O.N. Bodin, M.N. Kramm, D.V. Martynov

“…Therefore, the task of developing and researching methods for undistorted compression of medical data is an urgent scientific and applied task, due to the development and improvement of computing technology. …”

Inferring Travel Modes from Cellular Signaling Data Based on the Gated Recurrent Unit Neural Network by Yanchen Wang, Fei Yang, Li He, Haode Liu, Li Tan, Cheng Wang

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Establishment of two pathomic-based machine learning models to predict CLCA1 expression in colon adenocarcinoma. by Caiyun Yao, Maotong Hu, Lingxia Zhou, Hui Chen, Yang Cao

“…The objective of this research was to develop two pathomics models to predict CLCA1 expression from hematoxylin-eosin (H&E) stained pathological images and to investigate the biological mechanisms linked to pathomics features by associating the pathomics model with transcriptomic data. …”
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Destructive Creation of New Invasive Technologies: Generative Artificial Intelligence Behaviour by Mario Coccia

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Deep Learning Models for Rotated Object Detection in Aerial Images: Survey and Performance Comparisons by Jiaying He, K. L. Eddie Law

“…This study contributes to advancing the understanding of rotated object detection in aerial imagery by providing insights into effective methodologies and highlighting areas for future research. The findings guide practitioners and researchers in selecting appropriate techniques for applications requiring robust rotated object detection in challenging aerial environments.…”
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Harnessing AI and Quantum Computing for Revolutionizing Drug Discovery and Approval Processes: Case Example for Collagen Toxicity by David Melvin Braga, Bharat Rawal

“…Computational data methods could be used to reduce the cost and time involved in experimental drug discovery, allowing researchers to simulate biological interactions and screen large compound libraries more efficiently. …”
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Socio-Economical Analysis of a Green Reverse Logistics Network under Uncertainty: A Case Study of Hospital Constructions by Alireza Alibakhshi, Amirreza Saffarian, Erfan Hassannayebi

“…Despite the complexity of managing reverse logistics networks, this research provides valuable insights for supply chain planners. …”
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