The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review by Norah Hamad Alhumaidi, Doni Dermawan, Hanin Farhana Kamaruzaman, Nasser Alotaiq

“…A substantial portion of studies (n=38, 67%) focused on improving clinical decision-making, patient stratification, and treatment optimization. …”
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Reinforcement learning applications in water resource management: a systematic literature review by Linus Kåge, Vlatko Milić, Vlatko Milić, Maria Andersson, Magnus Wallén

“…Among the algorithms, deep Q-networks are the most commonly employed. …”
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Interval-Aware Scheduling of Surveillance Drones: Exact and Heuristic Approaches by Kaito Mori, Hiroki Nishikawa, Hiroyuki Tomiyama

“…In comparison to the Greedy method, the Multi-stage method achieved an average improvement of 37.8% in total flight time, while its algorithm runtime deteriorated by a maximum of 1.26 seconds. …”
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Modern advancements of energy storage systems integrated with hybrid renewable energy sources for water pumping application by Marwa M. Ahmed, Haneen M. Bawayan, Mohamed A. Enany, Mahmoud M. Elymany, Ahmed A. Shaier

“…Despite their potential, challenges such as renewable energy intermittency, optimal sizing, and cost-effectiveness are addressed. …”
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Enhanced Occupational Safety in Agricultural Machinery Factories: Artificial Intelligence-Driven Helmet Detection Using Transfer Learning and Majority Voting by Simge Özüağ, Ömer Ertuğrul

“…Subsequently, the extracted features were subjected to iterative neighborhood component analysis (INCA) for feature selection, after which they were classified using the k-nearest neighbor (kNN) algorithm. The classification outputs of all networks were combined through iterative majority voting (IMV) to achieve optimal results. …”
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Educational frontiers with ChatGPT: a social network analysis of influential tweets by Mehmet Firat, Saniye Kuleli

“… The unprecedented adoption of OpenAI's ChatGPT, marked by reaching 100 million daily users in early 2023, highlights the growing interest in AI for educational improvement. This research aims to analyze the initial public reception and educational impacts of ChatGPT, using social network analysis of the 100 most influential tweets. …”
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Elastic regularization networks for enhanced UAV visual tracking by Qingjiao Meng, Ji Li, Yan Jin, Zhaotian Deng

“…On the DTB70 dataset, the proposed method achieves a precision of 0.747 and a success rate of 0.789, representing improvements of 1% and 2.9%, respectively, over the STRCF algorithm. …”
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Synthesis of a reversible quantum Vedic multiplier on IBM quantum computers by Mojtaba Noorallahzadeh, Mohammad Mosleh

“…Abstract Quantum computers provide considerable potential to enhance computing technology, anticipated to surpass conventional computers by resolving intricate challenges that existing systems cannot tackle. They use quantum algorithms for improved performance and depend on reversible computations based on quantum physics and linear algebra. …”
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YOLOv9-GDV: A Power Pylon Detection Model for Remote Sensing Images by Ke Zhang, Ningxuan Zhang, Chaojun Shi, Qiaochu Lu, Xian Zheng, Yujie Cao, Xiaoyun Zhang, Jiyuan Yang

“…On the Satellite Remote Sensing Power Tower Dataset (SRSPTD), the YOLOv9-GDV algorithm achieves an mAP of 80.2%, representing a 4.7% improvement over the baseline algorithm. …”
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Exploring the Realization of Creative Dimensions within the Metaverse: The Case of Tabriz Metropolis by Saied Jaffari namvar, Hossein Nazmfar, Ibrahim Taghav

“…Based on the Aras Gray technique, regions 5, 8, and 10 were identified as the most optimal choices, while regions 6 and 9 were deemed less ideal. …”
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Physically-constrained evapotranspiration models with machine learning parameterization outperform pure machine learning: Critical role of domain knowledge. by Yeonuk Kim, Monica Garcia, T Andrew Black, Mark S Johnson

“…We found a strong correlation (r = 0.93) between the sensitivity of ET estimates to machine-learned parameters and model error (root-mean-square error; RMSE), indicating that reduced sensitivity minimizes error propagation and improves performance. Notably, the most accurate hybrid model (RMSE = 17.8 W m-2 in energy unit) utilized a novel empirical parameter, which is relatively stable due to land-atmosphere equilibrium, outperforming both the pure ML model and hybrid models requiring conventional parameters (e.g., surface conductance). …”
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Development of a robust FT-IR typing system for Salmonella enterica, enhancing performance through hierarchical classification by Diego Fredes-García, Javiera Jiménez-Rodríguez, Alejandro Piña-Iturbe, Pablo Caballero-Díaz, Tamara González-Villarroel, Fernando Dueñas, Aniela Wozniak, Aiko D. Adell, Andrea I. Moreno-Switt, Patricia García

“…The IR Biotyper was used to acquire spectra from these isolates. Machine learning algorithms, including support vector machines, were trained to classify the isolates. …”
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Analyzing Post-fire Vegetation Dynamics with Ultra-high Resolution Remote Sensing Data by O. Petrov, O. Petrov, A. Medvedev

“…Future research should focus on improving tree segmentation of SfM-MVS point clouds in dense canopies, optimizing co-alignment under varying environmental conditions, and integrating additional point cloud classification methods to improve accuracy in areas with complex species distribution.…”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…XGBoost emerged as the top performing algorithm, achieving an AUC of 0.94 and an accuracy of 0.875 on the test set, marking substantial improvements over previously reported best results. …”
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Comparison of artificial intelligence approaches for estimating wind energy production: A real-world case study by Mohamed Bousla, Mohamed Belfkir, Ali Haddi, Youness El Mourabit, Badre Bossoufi

“…The precise prediction of wind power is essential not only for the smooth integration into the power grid but also for the optimization of unit commitment, maintenance scheduling, and the improvement of power traders' profitability. …”
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Battery Energy Storage Systems in Microgrids: A Review of SoC Balancing and Perspectives by Thales Augusto Fagundes, Guilherme Henrique Favaro Fuzato, Lucas Jonys Ribeiro Silva, Augusto Matheus dos Santos Alonso, Juan C. Vasquez, Josep M. Guerrero, Ricardo Quadros Machado

“…In addition, this article explores optimization processes aimed at reducing operational costs while considering SoC equalization. …”
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Stunting Prediction Modeling in Toddlers Using a Machine Learning Approach and Model Implementation for Mobile Application by Eko Abdul Goffar, Rosa Eliviani, Lili Ayu Wulandhari

“…The models were trained and assessed using public datasets and the most effective algorithm was integrated into a mobile application for practical use. …”
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Bagging Vs. Boosting in Ensemble Machine Learning? An Integrated Application to Fraud Risk Analysis in the Insurance Sector by Ruixing Ming, Osama Mohamad, Nisreen Innab, Mohamed Hanafy

“…Notably, the combination of the Gradient Boosting Machine (GBM) algorithm with NCR re-sampling and GBMVI feature selection emerges as the most effective configuration, offering superior fraud detection capabilities. …”
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Statistical and Machine Learning Classification Approaches to Predicting and Controlling Peak Temperatures During Friction Stir Welding (FSW) of Al-6061-T6 Alloys by Assad Anis, Muhammad Shakaib, Muhammad Sohail Hanif

“…Some simulations showed temperatures exceeding the material’s melting point, indicating the need for improved thermal control. This was achieved by using three machine learning (ML) algorithms, i.e., Logistic Regression, k-Nearest Neighbors (k-NN), and Naive Bayes. …”
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Signal Mining and Analysis of Drug-Induced Myelosuppression: A Real-World Study From FAERS by Kaiyue Xia MM, Shupeng Chen MD, Yingjian Zeng MD, Nana Tang MD, Meiling Zhang MD

“…Conclusion This study identifies new DIM-related drug signals and emphasizes the need for early detection to improve clinical management and optimize treatment regimens. …”
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