High-throughput phenotyping tools for blueberry count, weight, and size estimation based on modified YOLOv5s by Xingjian Li, Sushan Ru, Zixuan He, James D. Spiers, Lirong Xiang

“…The first pipeline used traditional algorithms such as Hough Transform, Watershed, and filtering. …”
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Exploring the role of alternative lengthening of telomere-related genes in diagnostic modeling for non-alcoholic fatty liver disease by Nan Zhu, Xiaoliang Wang, Huiting Zhu, Yue Zheng

“…This study employed a support vector machine algorithm and least absolute shrinkage and selection operator regression analysis to identify key genes for constructing a diagnostic model. …”
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Goal-directed hemodynamic therapy in patients with colorectal cancer undergoing laparoscopic surgery by V. A. Panafidina, I. V. Shlyk

“…To estimate the efficacy of a modified algorithm of goal-directed hemodynamic management in patients with colorectal cancer who undergo laparoscopic surgery based on non-invasive monitoring of cardiac output.Subjects and methods. …”
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Extract optimization of Ulva lactuca L. and biological activities of optimized extracts by Nuh Korkmaz

“…In our study, the biological activities of extracts produced under the extract conditions that provided the highest biological activity of Ulva lactuca L. were determined. Methods Two different methods, Response Surface Method (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA) integration were used for optimization. …”
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Comparative Analysis of Automated Machine Learning for Hyperparameter Optimization and Explainable Artificial Intelligence Models by Muhammad Salman Khan, Tianbo Peng, Hanzlah Akhlaq, Muhammad Adeel Khan

“…One of the most significant challenges in AI lies in selecting and fine-tuning the optimal algorithm for a given task. Automated Machine Learning (AutoML) models have emerged as a promising solution to address this challenge by systematically exploring hyperparameter spaces to identify optimal configurations efficiently. …”
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Implementation Of Deep Learning Using Convolutional Neural Network Method In A Rupiah Banknote Detection System For Those With Low Vision by Dinul Akhiyar, Tukino Tukino, Sarjon Defit

“…For validation, 140 test images were utilized, which yielded an impressive mAP value of 97.5%. To further evaluate the system's reliability, tests were conducted under varying conditions, such as banknotes with creases, folds, or different lighting scenarios. …”
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Energy consumption forecasting and thermal insulator selection with random forest regression by Mohammed Fellah, Salma Ouhaibi, Naoual Belouaggadia, Khalifa Mansouri

“…In addition, a correlation analysis was conducted to identify the most influential characteristics on energy consumption, thereby enhancing the predictive performance of the model.The results show that the RF algorithm provides remarkable performance in predicting this performance index, with an R² accuracy of 84% and a mean absolute error of 0.02. …”
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Consistency and reliability of ultrasound-derived fat fraction in hepatic steatosis assessment: influence of posture and breathing variations by Tingjing You, Shengmin Zhang, Shuai Cheng, Zhenyu Shen

“…Methods A retrospective analysis was performed using the system with the UDFF algorithm. Two operators performed UDFF measurements in six different scenarios, each consisting of three measurements (18 in total). …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…These reservoir rock images are crucial for the digital characterization of the reservoir. We propose a novel algorithm consisting of the convolutional neural network, an attention mechanism, and a recurrent neural network for the reconstruction of reservoir rock or porous media images. …”
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Medium- Long-Term Runoff Forecasting Using Interpretable Hybrid Machine Learning Model for Data-Scarce Regions by YOU Yu-jun, BAI Yun-gang, LU Zhen-lin, ZHANG Jiang-hui, CAO Biao, LI Wen-zhong, YU Qi-ying

“…An Improved Particle Swarm Optimization (IPSO) algorithm was used to optimize this model, forming the IPSO-CNN-BiGRU-Attention hybrid model. …”
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Comprehensive Analysis of the Expression, Prognosis and Function of TRAF Family Proteins 
in NSCLC by Yixuan WANG, Qiang CHEN, Yaguang FAN, Shuqi TU, Yang ZHANG, Xiuwen ZHANG, Hongli PAN, Xuexia ZHOU, Xuebing LI

“…The expression levels of TRAF family members were closely associated with immune cell infiltration and stromal cell content in the tumor immune microenvironment, with varying positive and negative correlations among different members. Conclusion TRAF family members exhibit highly specific expression differences across different tissues and cancer types. …”
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The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review by Yuchen Ma, Mohan Li, Huiqun Wu

“…However, its role in predicting MACEs remains highly debated. ObjectiveWe evaluated the diagnostic value of ML models constructed using radiomic features extracted from CCTA in predicting MACEs, and compared the performance of different learning algorithms and models, thereby providing clinical recommendations for the diagnosis, treatment, and prognosis of MACEs. …”
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Analysis of global stock market development-Integration of clustering, classification, and shapley values. by Marcin Stawarz

“…This is followed by using the random forest algorithm to classify these clusters and evaluate the importance of various features. …”
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ANISOTROPIC REGULATOR OF DAMPING OF RANDOM VIBRATIONS OF THE MOBILE PLATFORM OF A BILAMENT VEHICLE APPARATUS by A. S. Abufanas, A. A. Lobaty, Yu. F. Yacina

“…The coefficients of the optimal regulator are obtained by mathematical modeling. As an example for evaluating the operability of the proposed algorithm, one of the control channels of the mobile platform, defined by a discrete mathematical model of the second order, is considered. …”
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Development and validation of a 3-D deep learning system for diabetic macular oedema classification on optical coherence tomography images by Mingzhi Zhang, Tsz Kin Ng, Yi Zheng, Guihua Zhang, Jian-Wei Lin, Ji Wang, Jie Ji, Peiwen Xie, Yongqun Xiong, Hanfu Wu, Cui Liu, Huishan Zhu, Jinqu Huang, Leixian Lin

“…The deep learning (DL) performance was compared with the diabetic retinopathy experts.Setting Data were collected from Joint Shantou International Eye Center of Shantou University and the Chinese University of Hong Kong, Chaozhou People’s Hospital and The Second Affiliated Hospital of Shantou University Medical College from January 2010 to December 2023.Participants 7790 volumes of 7146 eyes from 4254 patients were annotated, of which 6281 images were used as the development set and 1509 images were used as the external validation set, split based on the centres.Main outcomes Accuracy, F1-score, sensitivity, specificity, area under receiver operating characteristic curve (AUROC) and Cohen’s kappa were calculated to evaluate the performance of the DL algorithm.Results In classifying DME with non-DME, our model achieved an AUROCs of 0.990 (95% CI 0.983 to 0.996) and 0.916 (95% CI 0.902 to 0.930) for hold-out testing dataset and external validation dataset, respectively. …”
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Assessment of OLCI absorption coefficients for non-water components across all optical water classes by Astrid Bracher, Astrid Bracher, Andrew Clive Banks, Hongyan Xi, David Dessailly, Juan Gossn, Carole Lebreton, Rüdiger Röttgers, Ewa Kwiatkowska, Spyros Chaikalis, Ehsan Mehdipour, Elli Pitta, Mariana Altenburg Soppa, Jan Wevers, Christina Zeri

“…Additionally, based on a different type of retrieval, the absorption of coloured dissolved organic matter (CDOM) from the OLCI 443 nm band, acdom(443), has been introduced as a new product. …”
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Clinical effectiveness of routine first‐trimester combined screening for pre‐eclampsia in Spain with the addition of placental growth factor by Pablo Garcia‐Manau, Erika Bonacina, Berta Serrano, Sara Caamiña, Marta Ricart, Eva Lopez‐Quesada, Àngels Vives, Monica Lopez, Elena Pintado, Anna Maroto, Sara Catalan, Marta Dalmau, Ester Del Barco, Alina Hernandez, Marta Miserachs, Marta San Jose, Mireia Armengol‐Alsina, Elena Carreras, Manel Mendoza

“…First‐trimester screening using an algorithm that combines maternal characteristics, mean arterial blood pressure, uterine artery pulsatility index and biomarkers (pregnancy‐associated plasma protein‐A and placental growth factor) is the method that achieves a greater diagnostic accuracy. …”
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Comprehensive analysis of single-cell and bulk RNA sequencing data unveils antigen-presenting and processing fibroblasts and establishes a predictive model in gastric cancer by Chenggang Zhang, Fangqi Chen, Jie Li, Yixuan He, Juan Sun, Zicheng Zheng, Guanmo Liu, Yihua Wang, Weiming Kang, Xin Ye

“…CellChat algorithm was utilized to evaluate interactions between cells. …”
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An RTM-Driven Machine Learning Approach for Estimating High-Resolution FAPAR From LANDSAT 5/7/8/9 Surface Reflectance by Guodong Zhang, Gaofei Yin, Yi Zhang, Jiangchuan Hu, Zongyan Li, Changjing Wang, Dujuan Ma, Jiangliu Xie

“…This study synergized the strengths of RTM and machine learning algorithm while overcoming the limitations of RTM parameterization and generalization, providing an efficient and robust Landsat FAPAR estimation approach. …”
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A deep learning-orchestrated garlic routing architecture for secure telesurgery operations in healthcare 4.0 by Kavit Shah, Nilesh Kumar Jadav, Rajesh Gupta, Sucheta Gupta, Sudeep Tanwar, Joel J.P.C. Rodrigues, Fayez Alqahtani, Amr Tolba

“…A standard sensor dataset is utilized to train different AI algorithms, such as Long Short Term Memory (LSTM) and Gated Recurrent Neural Networks (GRU), for classifying malicious and non-malicious telesurgery data. …”
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