Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning by Qiqiang Liang, Xin Xu, Shuo Ding, Jin Wu, Man Huang

“…Multiple logistic regression (MLR) and machine learning algorithms were adopted to construct the prediction models.Results A total of 976 patients were included, with 349 patients successfully weaned off RRT. …”
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Stem-Leaf Segmentation and Morphological Traits Extraction in Rapeseed Seedlings Using a Three-Dimensional Point Cloud by Binqian Sun, Muhammad Zain, Lili Zhang, Dongwei Han, Chengming Sun

“…After pre-processing the rapeseed point clouds with denoising and segmentation, the plant height, leaf length, leaf width, and leaf area of the rapeseed in the seedling stage were extracted by a series of algorithms and were evaluated for accuracy with the manually measured values. …”
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Automated process assessment of primary healthcare for hyperlipidemia: preliminary findings and implications form Anhui, China by Ningjing Yang, Yuning Wang, Ying Li, Dongying Xiao, Ruirui Cui, Nana Li, Rong Liu, Jing Chai, Xingrong Shen, Debin Wang

“…., lipid lowering medication prescription) using self-designed algorithms. While the encounter-based measures included number or rate of visits for HL, currently-noticed hyperlipidemia (CNHL, or HL noticed during the current consultation), and ever-diagnosed hyperlipidemia (EDHL). …”
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Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

“…However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. Consequently, we propose the shuffle attention for you only look once version eight (SA-YOLOv8) model, which is based on an enhanced framework. …”
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Investigation of the physically unclonable function of a configurable ring oscillator by A. A. Ivaniuk

“…This serves as a foundation for exploring new methods and algorithms for calculating unique PUF responses.…”
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Optimizing AI Transformer Models for <italic>CO</italic>&#x2082; Emission Prediction in Self-Driving Vehicles With Mobile/Multi-Access Edge Computing Support by Javier Saez-Perez, Pablo Benlloch-Caballero, David Tena-Gago, Jose Garcia-Rodriguez, Jose Maria Alcaraz Calero, Qi Wang

“…This paper has introduced a novel approach that leverages Artificial Intelligence (AI) transformer architectures to predict CO2 emissions in Society of Automotive Engineers (SAE) Level 2 self-driving cars, surpassing the performance of previous algorithms. After examining and comparing the use of previously proposed LSTM-based and the proposed transformer architecture (CO2ViT), and identifying their strengths and limitations, we have explored the vehicular networking paradigm with the Mobile/Multi-Access Edge Computing (MEC) capabilities of 5G infrastructure to provide the prediction service of the proposed transformer model under different networking topologies. …”
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Diagnostic and prognostic value of inflammatory indices in patients with prediabetes and type 2 diabetes mellitus by Z.O. Shaienko, H.Yu. Morokhovets

“…Additional studies are needed to develop optimal threshold values of indices that will allow them to be included in standard algorithms for examining patients with impaired carbohydrate metabolism.…”
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Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke by Yanan Lin, Yan Li, Yayin Luo, Jie Han

“…We utilized the Random Forest (RF), Multilayer Perceptron (MLP), Adaptive Boosting (AdaBoost), and Gaussian Naive Bayes (GauNB) algorithms to develop ML-HT models. The models' predictive performance was evaluated using confusion matrix (including accuracy, precision, recall, and F1 score), and discriminative analysis (area under the receiver-operating-characteristic curve, ROC-AUC) in the original cohort, followed by validation in an independent external cohort. …”
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Classification of single tree decay stages from combined airborne LiDAR data and CIR imagery by Tsz-Chung Wong, Abubakar Sani-Mohammed, Jinhong Wang, Puzuo Wang, Wei Yao, Marco Heurich

“…Finally, the classification is conducted on the two datasets (3D multispectral point clouds and 2D projected images) based on the three ML algorithms. All models achieved promising results, reaching overall accuracy (OA) of up to 88.8%, 88.4% and 85.9% for KPConv, CNN and RF, respectively. …”
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Comprehensive Multi-indicator Prediction Model for Storage Quality of Multi-cultivar Kiwifruit Based on Visible-Near Infrared Spectroscopy by Zizhao LIANG, Xin LI, Pu LIU, Wenqiang GUAN, Ming LI

“…After the use of different preprocessing algorithms, such as first-order derivatives (FD), standard normal variate (SNV), second-order derivatives, convolutional smoothing, and FD+SNV, the data were combined with competitive adaptive reweighted sampling (CARS) for feature wavelength selection. …”
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Sustainable Innovation: Harnessing AI and Living Intelligence to Transform Higher Education by Hesham Mohamed Allam, Benjamin Gyamfi, Ban AlOmar

“…However, while AI has the potential to improve education significantly, it also introduces challenges, such as ethical concerns, data privacy risks, and algorithmic bias. The real challenge is not just about embracing AI’s benefits but ensuring it is used responsibly, fairly, and in a way that aligns with educational values. …”
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LSTM-Enhanced Deep Reinforcement Learning for Robust Trajectory Tracking Control of Skid-Steer Mobile Robots Under Terra-Mechanical Constraints by Jose Manuel Alcayaga, Oswaldo Anibal Menéndez, Miguel Attilio Torres-Torriti, Juan Pablo Vásconez, Tito Arévalo-Ramirez, Alvaro Javier Prado Romo

“…Four state-of-the-art DRL algorithms, i.e., Proximal Policy Optimization (PPO), Deep Deterministic Policy Gradient (DDPG), Twin Delayed DDPG (TD3), and Soft Actor–Critic (SAC), are selected to evaluate their ability to generate stable and adaptive control policies under varying environmental conditions. …”
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Analyzing Random Forest&#x2019;s Predictive Capability for Type 1 Diabetes Progression by Niels F. Cleymans, Mark Van De Casteele, Julie Vandewalle, Aster K. Desouter, Frans K. Gorus, Kurt Barbe

“…This explorative study aims to uncover the potential of random forest machine learning algorithms as survival models within the biomedical context of T1D. …”
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Amyloid Cardiomyopathy: Review of A Fatal Case Report by O. V. Soldatova, I. Ya. Goryanskaya

“…The relevance of this topic is due to the need to improve diagnostic algorithms and reduce the time for primary diagnosis of amyloid cardiomyopathy in order to improve the prognosis of the disease.We have described a clinical case of an elderly patient with a torpid course of progressive decompensation of congestive heart failure, which ended fatally on the 3rd day of hospitalization. …”
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Multiphase Computed Tomography Scan Findings for Artificial Intelligence Training in the Differentiation of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on In... by Nakarin Inmutto, Suwalee Pojchamarnwiputh, Wittanee Na Chiangmai

“…<b>Conclusions:</b> Cirrhosis and lymph node metastasis could be ancillary and adopted in future AI training algorithms.…”
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Analysis of spatio-temporal fungal growth dynamics under different environmental conditions by Liselotte De Ligne, Guillermo Vidal-Diez de Ulzurrun, Jan M. Baetens, Jan Van den Bulcke, Joris Van Acker, Bernard De Baets

“…Fortunately, more automated ways of measurement are gaining momentum due to the availability of cheap imaging and processing equipment and the development of dedicated image analysis algorithms. In this paper, we use image analysis to assess the impact of environmental conditions on the growth dynamics of two economically important fungal species, Coniophora puteana and Rhizoctonia solani. …”
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Using large language models for enhanced fraud analysis and detection in blockchain based health insurance claims by Ruba Islayem, Senay Gebreab, Walaa AlKhader, Ahmad Musamih, Khaled Salah, Raja Jayaraman, Muhammad Khurram Khan

“…The architecture, sequence diagrams, and implementation algorithms outline the development process, while testing scenarios demonstrate the system’s ability to detect fraud such as inflated costs, unnecessary treatments, and unrendered services. …”
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Growth dynamics of splenic artery aneurysms: morphology, comorbidities, and vascular anatomical factors by Ahmet Tanyeri, Aygün Katmerlikaya, Rıdvan Akbulut, Mehmet Burak Çildağ

“…Guidelines should be refined and strengthened with patient-specific follow-up and treatment algorithms based on updated clinical data. Clinical trial number Not applicable.…”
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A “giant bomb” in acute myocardial infarction due to coronary artery aneurysm: a case report by Jin Chen, Wei Du, Jianyu Jiang, Liugang Xu, Liugang Xu

“…While existing literature describes therapeutic applications of surgical repair, percutaneous intervention, and pharmacotherapy in coronary artery aneurysm management, no consensus-driven protocol has been established, reflecting critical knowledge gaps in risk-stratified treatment algorithms for thrombus-laden aneurysms.Case outlineA 51-year-old female presenting with acute ST-segment elevation myocardial infarction underwent emergency coronary angiography, revealing a large right coronary artery aneurysm with significant intra-aneurysmal thrombus burden. …”
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Quantifying leaf symptoms of sorghum charcoal rot in images of field‐grown plants using deep neural networks by Emmanuel M. Gonzalez, Ariyan Zarei, Sebastian Calleja, Clay Christenson, Bruno Rozzi, Jeffrey Demieville, Jiahuai Hu, Andrea L. Eveland, Brian Dilkes, Kobus Barnard, Eric Lyons, Duke Pauli

“…The objective of this work was to implement various machine learning algorithms to evaluate their ability to accurately detect and quantify CRS in red‐green‐blue images of sorghum plants exhibiting symptoms of infection. …”
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