A Novel Approach for Improving Cloud Liquid Water Content Profiling with Machine Learning by Anas Amaireh, Yan (Rockee) Zhang, Pak Wai Chan, Dusan Zrnic

“…The methodology was tested across multiple ML algorithms, with ensemble models such as Bagged Trees demonstrating superior predictive accuracy and robustness. …”
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The identification and validation of histone acetylation-related biomarkers in depression disorder based on bioinformatics and machine learning approaches by Lu Zhang, Lu Zhang, YuJing Lv, Mengqing Ma, Jile Lv, Jie Chen, Shang Lei, Yi Man, Guimei Xing, Yu Wang

“…Three hub genes (JDP2, ALOX5, and KPNB1) were gained by two machine learning algorithms. The nomogram constructed based on these three hub genes showed high predictive accuracy. …”
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Design, Fabrication, and Application of Large-Area Flexible Pressure and Strain Sensor Arrays: A Review by Xikuan Zhang, Jin Chai, Yongfu Zhan, Danfeng Cui, Xin Wang, Libo Gao

“…Real-time data processing requires innovative solutions such as edge computing and machine learning algorithms, ensuring low-latency, high-accuracy data interpretation while preserving the flexibility of sensor arrays. …”
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Urban Expansion and Land Use Transformations in Midnapore City (2003–2024): Implications for Sustainable Development by Rakesh Ranjan Thakur, Debabrata Nandi, Anoop Kumar Shukla, Subhasmita Das, Sasmita Chand, Pankaj Singha, Roshan Beuria, Chetan Sharma

“…These factors led to the reduction of LULC classes possessing substantial ecological value like forests and scrub lands which are becoming more accessible due to the increasing population. …”
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Antibacterial therapy of pyogenic liver abscesses by V. V. Novak, V. O. Belinska

“…To study the features of the microbial landscape, to develop an algorithm for antibacterial therapy in patients with pyogenic liver abscesses. …”
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Digital literacy curriculum transformation to overcome filter bubble in Pancasila character understanding by A. Achdyat, Dasim Budimansyah, Encep Syarif Nurdin, Mupid Hidayat

“…The impact is seen in the homogenization of information, strengthening of confirmation bias, and polarization of understanding, which has the potential to cause distortion of Pancasila values, so digital literacy, algorithm transparency, and transformation of the education curriculum are needed to overcome it.    …”
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Digital Reconstruction Method for Low-Illumination Road Traffic Accident Scenes Using UAV and Auxiliary Equipment by Xinyi Zhang, Zhiwei Guan, Xiaofeng Liu, Zejiang Zhang

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Data source and utilization of artificial intelligence technologies in vascular surgery—a scoping review by Katarzyna Powezka, Katarzyna Powezka, Katarzyna Powezka, Karin Slater, David Brind, Michael Wall, Michael Wall, Georgios Gkoutos, Maciej Juszczak, Maciej Juszczak

“…Image-based data were utilised in 216 articles, while 153 and 85 papers relied on medical records, and clinical parameters. The AI algorithms were used for predictive modelling (123 papers), medical image segmentation (118), and to aid identification, detection, and diagnosis (103).DiscussionApplications of Artificial Intelligence (AI) are gaining traction in healthcare, including vascular surgery. …”
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Potential of machine learning methods in operational risk stratification in patients with coronary artery disease scheduled for coronary bypass surgery by E. Z. Golukhova, M. A. Keren, T. V. Zavalikhina, N. I. Bulaeva, D. S. Akatov, I. Yu. Sigaev, K. B. Yakhyaeva, D. A. Kolesnikov

“…Five machine learning (ML) algorithms were used to build predictive risk models: Logistic regression, Random Forrest, CatBoost, LightGBM, XGBoost. …”
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Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data by S. R. Mani Sekhar, D. M. Mushtaq Ahmed, G. M. Siddesh

“…The result shows that the proposed air pollution model predicted 96.06700 PM2.5 concentration levels, subsequently the temperature model predicted 14.06800∘C. …”
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Identification of Spambots and Fake Followers on Social Network via Interpretable AI-Based Machine Learning by Danish Javed, Noor Zaman Zaman, Navid Ali Khan, Sayan Kumar Ray, Arafat Al-Dhaqm, Victor R. Kebande

“…Most of the current bot detection methods rely on black-box algorithms, raising concerns about their transparency and practical usability. …”
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Role of artificial intelligence in earlier diagnosis of bronchopulmonary dysplasia by Lam Q. Bui, Sandhya J. Kadam

“…A deep learning component can be used for lung segmentation of preterm chest radiographs to build a BPD prediction model by focusing on lung anatomy. This article explains the criteria used for BPD diagnosis and compares them with AI-based algorithms, especially for accuracy, applicability, and efficiency. …”
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A generalized linear model for estimating spectrotemporal receptive fields from responses to natural sounds. by Ana Calabrese, Joseph W Schumacher, David M Schneider, Liam Paninski, Sarah M N Woolley

“…In the auditory system, the stimulus-response properties of single neurons are often described in terms of the spectrotemporal receptive field (STRF), a linear kernel relating the spectrogram of the sound stimulus to the instantaneous firing rate of the neuron. Several algorithms have been used to estimate STRFs from responses to natural stimuli; these algorithms differ in their functional models, cost functions, and regularization methods. …”
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Artificial intelligence driven innovations in biochemistry: A review of emerging research frontiers by Mohammed Abdul Lateef Junaid

“…Key AI techniques—such as machine learning algorithms, natural language processing, and AI-based molecular modeling—are discussed. …”
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Cardiac disease diagnosis based on GAN in case of missing data. by Xing Chen, Na Zhang, Xiaohui Yang, Chunyan Wang, Qi Na, Tianyun Luan, Wendi Zhu, Chenjie Zhang, Chao Yang

“…The experimental results demonstrate that compared to other filling algorithms, the data matrix filled by the proposed algorithm in this paper has more evident practical significance, fewer errors, and higher accuracy in downstream classification prediction.…”
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adm: An R package for constructing abundance‐based species distribution models by Admir Cesar deOliveira Junior, Santiago José Elías Velazco

“…Here, we present the adm R package developed to support the construction of ADM, including data preparation, model fitting, prediction and model exploration. This package offers several modelling approaches (i.e. algorithms) that can be fine‐tuned and customized. …”
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Yield Response of Different Rice Ecotypes to Meteorological, Agro-Chemical, and Soil Physiographic Factors for Interpretable Precision Agriculture Using Extreme Gradient Boosting a... by Md. Sabbir Ahmed, Md. Tasin Tazwar, Haseen Khan, Swadhin Roy, Junaed Iqbal, Md. Golam Rabiul Alam, Md. Rafiul Hassan, Mohammad Mehedi Hassan

“…Moreover, this study found a different set of those factors with respect to the yield response of different rice ecotypes. Machine learning algorithms named Extreme Gradient Boosting (XGBoost) and Support Vector Regression (SVR) have been used for predicting the yield response. …”
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Service Function Chain Migration: A Survey by Zhiping Zhang, Changda Wang

“…Existing approaches have demonstrated promising results in both passive and active migration strategies, leveraging techniques such as reinforcement learning for dynamic scheduling and digital twins for resource prediction. Nonetheless, critical issues remain—particularly regarding service interruption control, state consistency, algorithmic complexity, and security and privacy concerns. …”
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An Analysis of Novel Money Laundering Data Using Heterogeneous Graph Isomorphism Networks. FinCEN Files Case Study by Filip Wójcik

“…The proposed model outperformed other algorithms in terms of F1 score, precision, and ROC AUC in both training and testing phases. …”
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A Survey on Machine Learning Approaches for Personalized Coaching with Human Digital Twins by Harald H. Rietdijk, Patricia Conde-Cespedes, Talko B. Dijkhuis, Hilbrand K. E. Oldenhuis, Maria Trocan

“…Preliminary investigations revealed a significant difference in performance, as measured by prediction accuracy and F1-score, between the optimal choice of machine learning algorithms for generalized and personalized processing of the available data. …”
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