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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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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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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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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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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Prediction of environmental suitability for Haematoxylum campechianum: A proposal to promote reforestation in Mexico by Anay Serrano-Rodríguez, Annery Serrano Rodríguez, Yarelys Ferrer-Sánchez, Fernando Abasolo-Pacheco, Mariela Alexi Díaz Ponce, Norma María Guerrero Chuez, Pedro Harrys Lozano Mendoza, Alexis Herminio Plasencia-Vázquez

“…For this purpose, we included 638 occurrence points and used the MaxEnt algorithm for modeling, analyzing different parameters. …”
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Digital innovation in healthcare: quantifying the impact of digital sepsis screening tools on patient outcomes—a multi-site natural experiment by Sarah Tonkin-Crine, Graham Cooke, Anthony C Gordon, Anthony Gordon, Shashank Patil, Runa Lazzarino, Andrew Brent, Kate Honeyford, Céire E Costelloe, Anne Kinderlerer, John Welch, Peter Ghazal, Claire Burnett, Alf Timney, Andrew Jonathan Brent, Cerie Costelloe, Pippa Goodman Ben Glampson

“…Introduction The National Health Service (NHS) ‘move to digital’ incorporating electronic patient record systems (EPR) facilitates the translation of paper-based screening tools into digital systems, including digital sepsis alerts. We evaluated the impact of sepsis screening tools on in-patient 30-day mortality across four multi-hospital NHS Trusts, each using a different algorithm for early detection of sepsis.Methods Using quasi-experimental methods, we investigated the impact of the screening tools. …”
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Does Artificial Intelligence Bring New Insights in Diagnosing Phlebological Diseases?—A Systematic Review by Sergiu-Ciprian Matei, Sorin Olariu, Ana-Maria Ungureanu, Daniel Malita, Flavia Medana Petrașcu

“…Notably, AI algorithms have achieved an accuracy exceeding 90%, significantly reducing inter-observer variability and ensuring consistent interpretation of ultrasonographic images across different clinicians and settings. …”
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Deep learning object detection-based early detection of lung cancer by Kuo-Yang Huang, Kuo-Yang Huang, Kuo-Yang Huang, Che-Liang Chung, Che-Liang Chung, Che-Liang Chung, Jia-Lang Xu

“…The Lung-PET-CT-Dx public dataset was used for the model training and evaluation. The performance of the You Only Look Once (YOLO) series of models in the lung CT image object detection task is compared in terms of algorithms, and different versions of YOLOv5, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 are examined for lung cancer detection and classification. …”
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The Significance of MAPK Signaling Pathway in the Diagnosis and Subtype Classification of Intervertebral Disc Degeneration by Yong Liu, Xueyan Chen, Jingwen Chen, Chao Song, Zhangchao Wei, Zongchao Liu, Fei Liu

“…Additionally, we applied PPI networks, LASSO analysis, the RF algorithm, and the SVM‐RFE algorithm to identify core MAPK‐related genes. …”
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Adaptive User Pairing With Non-Orthogonal Medium Access Choices for Balanced Coexistence of Mission-Critical and eMBB Services in Cellular IoT by Farnaz Khodakhah, Aamir Mahmood, Patrik Osterberg, Mikael Gidlund

“…To realize different spatial associations among users in the cell, the proposed pairing strategy for eMBB and MC services is evaluated for three user distributions around the base station: concave (eMBB users concentrated near the BS), uniform (evenly spread eMBB and MC users), and convex (MC users concentrated near the BS). …”
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