Unlocking biological complexity: the role of machine learning in integrative multi-omics by Ravindra Kumar, Rajrani Ruhel, Andre J. van Wijnen

“…It offers sophisticated algorithms that can identify and discover hidden patterns and provide insights into complex biological networks. …”
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A New High-Performance Photovoltaic Emulator Suitable for Simulating and Validating Maximum Power Point Tracking Controllers by Ambe Harrison, Njimboh Henry Alombah

“…Currently, researchers face several challenges in testing MPPT algorithms due to the unpredictable nature of solar PV power generation. …”
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An Interpretable Machine Learning-Based Hurdle Model for Zero-Inflated Road Crash Frequency Data Analysis: Real-World Assessment and Validation by Moataz Bellah Ben Khedher, Dukgeun Yun

“…The first stage uses binary classification to identify road segments with potential crash occurrences, applying a customized loss function to tackle data imbalance. The second stage predicts crash frequency, also utilizing a customized loss function for count data. …”
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COMPARATIVE EVALUATION OF INDICATORS OF STRUCTURAL AND MECHANICAL PROPERTIES OF WHEAT GRAIN by P. V. Medvedev, V. A. Fedotov, E. S. Lukyanova

“…The vitreous nature of wheat allows us to predict the bakery and pasta advantages of flour from this grain. …”
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FedQP: Large-Scale Private and Flexible Federated Query Processing by Hussain M. J. Almohri, Layne T. Watson

“…The key challenge is in designing algorithms that efficiently aggregate client input, minimize data exposure, and maximize model adaptability. …”
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Enhancing action recognition in educational settings using AI-driven information systems for public health monitoring by Changchun Lu, Han Ruijuan

“…Traditional methods, which primarily rely on rule-based algorithms or handcrafted feature extraction, face significant challenges in adaptability, scalability, and real-time processing. …”
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A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics by Shnain Ammar H., Mohammed G., Kumar Yalla Jeevan Nagendra

“…To solve these challenges, CM-IoT-SN combines a network of IoT-enabled sensors continuously monitoring key environmental factors such as soil moisture, temperature, and nutrient levels. Advanced algorithms then utilize the realtime data acquired to provide farmers expected insights and quick advise.CM-IoT-SNs adoption across many test locations has proved its effectiveness in producing superior decision-making in crop management by means of exact, real-time monitoring and predictive analytics. …”
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Ethical Challenges of Using the Internet of Behavior in the Medical and Healthcare Practice by Zahra Sadeqi-Arani, Esmaeil Mazroui Nasrabadi

“…Additionally, reliance on algorithms for IoB data analysis should not diminish human oversight in healthcare decision-making. …”
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Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis. by Nabila Kazmi, Tom R Gaunt

“…With the recent advances in genomic tools and technologies there is potential to predict and diagnose heart disease using molecular data from analysis of blood cells. …”
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Intelligent Processing Methods by Veronika V. Tolmanova, Denis A. Andrikov

“…These methods, together with modern algorithms and computer models, allow extracting valuable information from huge volumes of raw data, as well as analyzing and forecasting various phenomena and trends. …”
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Transcriptome signature for multiple biotic and abiotic stress in barley (Hordeum vulgare L.) identifies using machine learning approach by Bahman Panahi

“…Machine learning models, specifically Random Forest and C4.5, were optimized and evaluated using a 10-fold cross-validation approach. The C4.5 algorithm demonstrated superior accuracy in predicting stress-responsive signatures. …”
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Forest Fire Hazard Assessment using Remote Sensing Data and Machine Learning, Case Study of Jijel, Algeria by Matougui Zakaria, Zouidi Mohamed

“…This paper assesses wildfire hazards in Jijel, Algeria, using advanced machine learning techniques combined with spatial analysis of environmental and anthropogenic factors. Two algorithms, K-Nearest Neighbours (KNN) and Histogram-Based Gradient Boosting (HGB), were employed. …”
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Identification and validation of TUBB, CLTA, and FBXL5 as potential diagnostic markers of postmenopausal osteoporosis by Yue Tan, Yujing Wang, Qin Zhu, Yan Xue, Xuhao Ji, Zhenkun Li, Jiawen Shen, Chengming Sun, Shiqi Ren, Chenlin Zhang, Jianfeng Chen

“…Additionally, we intersected the clusters to identify differentially expressed genes (DEGs) and analyzed potential diagnostic markers for PMOP using support vector machine recursive feature elimination (SVM-RFE), LASSO, and random forest (RF) algorithms, which were subsequently validated in the GSE56116 dataset. …”
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Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…The findings underscore the significant potential of optimized machine learning approaches in predicting extreme events, such as wildfires, and improving fire management strategies. …”
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Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography by Ruiting Jia, Baozhi Liu, Mohsin Ali

“…The diagnostic accuracy was 90.58%, with an overall positive predictive value of 89% and an overall negative predictive value of 86%. …”
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Critical Review and Benchmark Proposal on FE Modeling for Patch Loading Resistance of Slender Steel Plate Girders in Launched Bridges by Marck Anthony Mora Quispe

“…It provides a comprehensive description of an FE model that accurately predicts both the load–displacement behavior and the patch loading resistance. …”
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LoD2 Building Reconstruction from Stereo Satellite Imagery using Deep Learning and Model-Driven Approach by Rojgar Qarani Ismael, Haval Sadeq

“…The suggested methodology is tested on the GeoEye-1 satellite imagery dataset for Erbil City, which is validated with ground truth data. The proposed algorithm presented promising results, it is shown that the model can predict building heights for ridge and eave to a mean absolute error of 0.70 m, and in the occluded area was approximately 1.0 m. …”
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Nasopharyngeal Carcinoma Subtype Discovery via Immune Cell Scores from Tumor Microenvironment by Yanbo Sun, Yun Liu, Hanqi Chu

“…Machine learning models, including random forest (RF) and support vector machine (SVM) algorithms, were constructed to predict the immune subtype. …”
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Aircraft maintenance system simulation mathematical model construction by Yu. I. Samulenkov, Ya. A. Filatova, A. D. Gruzd

“…The proposed simulation model can be used for the aircraft technical condition predictive estimate, aircraft gas turbine engines and functional systems.…”
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Modeling Estuarine Algal Bloom Dynamics with Satellite Data and Spectral Index-Based Classification by Mayya Podsosonnaya, Maria J. Schreider, Sergei Schreider

“…This can be achieved by implementation of processing algorithms and indices on multi-spectral satellite images. …”
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