Prediction of Diabetes in Middle-Aged Adults: A Machine Learning Approach by Gideon Addo, Bismark Amponsah Yeboah, Michael Obuobi, Raphael Doh-Nani, Seidu Mohammed, David Kojo Amakye

“…Future research should explore genetic, lifestyle, and environmental factors to improve diagnostic accuracy.…”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…Through rigorous analysis, the properties with the most significant influence on solubility were identified and subsequently used as input features for four ensemble machine learning algorithms: Random Forest, Extra Trees, XGBoost, and Gradient Boosting. …”
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Blockchain-Assisted Verifiable and Multi-User Fuzzy Search Encryption Scheme by Xixi Yan, Pengyu Cheng, Yongli Tang, Jing Zhang

“…Locality-sensitive hashing and bloom filters are used to realize multi-keyword fuzzy search, and the bigram segmentation algorithm is optimized for keyword conversion to improve search accuracy. …”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…Special attention is given to de novo drug design using generative adversarial networks (GANs) and variational autoencoders (VAEs), as well as AI-driven high-throughput virtual screening that reduces computational costs while improving hit identification. The review also discusses platforms like Deep-PK and DeepTox for pharmacokinetics and toxicity prediction using graph-based descriptors and multitask learning. …”
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A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications by Gege Ding, Jiayue Liu, Dongsheng Li, Xiaming Fu, Yucheng Zhou, Mingrui Zhang, Wantong Li, Yanjuan Wang, Chunxu Li, Xiongfei Geng

“…The CFSD-UAVNet model was evaluated on the publicly available SeaDronesSee maritime dataset and compared with other cutting-edge algorithms. The experimental results showed that the CFSD-UAVNet model achieved an mAP@50 of 80.1% with only 1.7 M parameters and a computational cost of 10.2 G, marking a 12.1% improvement over YOLOv8 and a 4.6% increase compared to DETR. …”
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A longan-picking sequence planning method for UAV system based on multi-target tracking by Kaixuan Wu, Meiqi Zhang, Linlin Shi, Hengxu Chen, Yuju Mai, Mingda Luo, Hengyi Lin, Jun Li

“…A LonTsp planning algorithm is used for path planning, optimizing picking paths to reduce total picking time by 19.1% and lowering UAV energy consumption and time costs. …”
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Simplified Pedestrian Tracking Filters with Positioning and Foot-Mounted Inertial Sensors by Henar Martin, Juan A. Besada, Ana M. Bernardos, Eduardo Metola, José R. Casar

“…Pedestrian tracking is one of the bases for many ubiquitous context-aware services, but it is still an open issue in indoor environments or when GPS estimations are not optimal. In this paper, we propose two novel different data fusion algorithms to track a pedestrian using current positioning technologies (i.e., GPS, received signal strength localization from Wi-Fi or Bluetooth networks, etc.) and low cost inertial sensors. …”
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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…The results demonstrate that OLVGP not only substantially reduces computational costs compared to traditional sparse GP methods but also dynamically adapts to the evolving data, delivering improved performance in time series prediction.…”
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Drowsiness Detection of Construction Workers: Accident Prevention Leveraging Yolov8 Deep Learning and Computer Vision Techniques by Adetayo Olugbenga Onososen, Innocent Musonda, Damilola Onatayo, Abdullahi Babatunde Saka, Samuel Adeniyi Adekunle, Eniola Onatayo

“…The system improves productivity and reduces costs by preventing accidents and enhancing worker safety. …”
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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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Obstacle avoidance and formation control of multiple unmanned vehicles in complex environments based on artificial potential field method by Yilin MEI, Likun CUI, Xueyan HU, Guangqi HU, Hao WANG

“…Specifically, the success rate of obstacle avoidance in dynamic environments increased by 35% compared to traditional algorithms and by 10% compared to improved algorithms. …”
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Development of Machine Learning Prediction Models to Predict ICU Admission and the Length of Stay in ICU for COVID‑19 Patients Using a Clinical Dataset Including Chest Computed Tom... by Seyed Salman Zakariaee, Negar Naderi, Hadi Kazemi-Arpanahi

“…Timely prediction of ICU admission and ICU LOS of COVID-19 patients would improve patient outcomes and lead to the optimal use of limited hospital resources.…”
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Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…The multiple imputation method creates for each missing value not one, but many imputations, which avoids a systematic error, but at the expense of high computational costs. For the initial data used in the work, the best result was shown by the implementation of the multiple imputation algorithm based on the detected outliers by the support vector method.Conclusion. …”
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“Bias Correction Method” for Regional Correction Experiment of Warm Season Rainstorm in Zhejiang by Chengyan Mao, Xin Pan, Haowen Li, Weibiao Li, Haoya Liu

“…The correction has the most significant impact in northwestern Zhejiang, while its effects are less pronounced in the northeastern coastal areas. (2) Both overall correction and regional correction improve forecast accuracy across various precipitation thresholds. …”
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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…Thus, preserving features that carry the most relevant information at each scale is crucial for improving counting precision. …”
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Countermeasuring Anti-Ship Missiles for Surface Naval Platforms: A Machine Learning Approach With Explainable Artificial Intelligence by Murat Ertop, Ali Oter, Ali Kara

“…The effective deployment of existing countermeasures and the determination of the most optimal platform maneuvers have also become crucial. …”
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A Framework for Autonomous UAV Navigation Based on Monocular Depth Estimation by Jonas Gaigalas, Linas Perkauskas, Henrikas Gricius, Tomas Kanapickas, Andrius Kriščiūnas

“…The solution utilizes a depth image estimation model to create an occupancy grid map of the surrounding area and uses an A* path planning algorithm to find optimal paths to end goals while navigating around the obstacles. …”
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Implementation of XGBoost Models for Predicting CO₂ Emission and Specific Tractor Fuel Consumption by Nebojša Balać, Zoran Mileusnić, Aleksandra Dragičević, Mihailo Milanović, Andrija Rajković, Rajko Miodragović, Olivera Ećim-Đurić

“…The CO₂ prediction model achieved an accuracy exceeding 80%, while the model for fuel consumption reached over 65%. Although not optimized for high precision, these models offer a valuable basis for preliminary assessments and highlight the potential of data-driven approaches for improving energy efficiency and environmental sustainability in agricultural mechanization.…”
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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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CPFD Simulation of Operation Characteristics of a 10t/d Sludge and Biomass Co-incineration Fluidized Bed Reactor by REN Shaohui, YU Qiao, LIN Li, XIANG Jiatao, MA Lun, ZHANG Shihong

“…Higher bed temperatures (750→850℃) enhanced fuel conversion (CO₂↑12.03→13.46%) and H₂S oxidation (↓0.20→0.16%), while increased bed height (400→600 mm) paradoxically raised CNO by 57% despite improved residence time, suggesting channeling issues. …”
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