Artificial liver classifier: a new alternative to conventional machine learning models by Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid

“…To optimize the ALC's parameters, an improved FOX optimization algorithm (IFOX) is employed during training.ResultsWe evaluate the proposed ALC on five benchmark datasets: Iris Flower, Breast Cancer Wisconsin, Wine, Voice Gender, and MNIST. …”
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Automatic Fall Risk Detection Based on Imbalanced Data by Yen-Hung Liu, Patrick C. K. Hung, Farkhund Iqbal, Benjamin C. M. Fung

“…Since fall data is rare in real-world situations, we train and evaluate our approach in a highly imbalanced data setting. …”
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Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

“…The dataset was split into training and test sets in a 70-30 ratio. Five machine learning models were trained and evaluated using metrics such as accuracy, precision, recall, F1-score, and ROC-AUC. …”
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MOTH: Memory-Efficient On-the-Fly Tiling of Histological Image Annotations Using QuPath by Thomas Kauer, Jannik Sehring, Kai Schmid, Marek Bartkuhn, Benedikt Wiebach, Slaven Crnkovic, Grazyna Kwapiszewska, Till Acker, Daniel Amsel

“…This enables algorithms to count, measure, or evaluate those areas when trained properly. …”
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A Comparative Study of Machine Learning Based Classifications on Lung Cancer Detection by A. Rakesh, Radhamani Ellapparaj

“…Through meticulous phases of model development, training, validation, and testing, this study evaluates the performance and accuracy of the proposed models. …”
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Planning and layout of tourism and leisure facilities based on POI big data and machine learning. by Shifeng Wu, Jiangyun Wang, Yinuo Jia, Jintian Yang, Jixiu Li

“…Secondly, the decision-making model, trained with the CART algorithm, reveals that accommodation availability, shopping choices, and transportation infrastructure significantly influence the siting of tourism and leisure facilities in Beijing's urban core. …”
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Analysis and Prediction of Grouting Reinforcement Performance of Broken Rock Considering Joint Morphology Characteristics by Guanglin Liang, Linchong Huang, Chengyong Cao

“…Notably, the Random Forest (RF) algorithm excels in rapid and accurate predictions when handling similar training data, while the ANN-based MCD algorithm consistently delivers stable and precise results across diverse datasets.…”
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Predictive value of the stone-free rate after percutaneous nephrolithotomy based on multiple machine learning models by Zhao Rong Liu, Zhao Rong Liu, Zhan Jiang Yu, Jie Zhou, Jian Biao Huang

“…Three ML models (GBDT, RF, and XGBoost) were developed using the training set. The predictive performance of these models was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) on the test set, confusion matrix, specificity, sensitivity, accuracy, and F1 score. …”
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Identification of biomarkers for Laryngeal squamous cell carcinoma through Mendelian randomization and integrated bioinformatics analysis by Pengjian Zhang, Weizhang Chen, Kai Chen, Yuanhang Ye, Weijun Wu

“…RNA-seq data from 114 LSCC and 12 normal samples were collected from the TCGA-HNSC cohort as a training set, while 270 LSCC samples were obtained from the GSE65858 dataset as a validation set. …”
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Computed tomography-based radiomic features combined with clinical parameters for predicting post-infectious bronchiolitis obliterans in children with adenovirus pneumonia: a retro... by Li Zhang, Ling He, Guangli Zhang, Xiaoyin Tian, Haoru Wang, Fang Wang, Xin Chen, Yinglan Zheng, Man Li, Yang Li, Zhengxiu Luo

“…Combined models based on radiomic and clinical features were established via logistic regression (LR), random forest (RF), and support vector machine (SVM) algorithms. Model performance was evaluated via the area under the receiver operating characteristic curve (AUC). …”
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Are Re-Ranking in Retrieval-Augmented Generation Methods Impactful for Small Agriculture QA Datasets? A Small Experiment by Akbar Nur Arifin

“…The efficacy of their algorithm across a range of QDMR transformation tasks was evaluated, and the experiment evaluation showed that rereading did not significantly increase performance over baselines. …”
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DFDA-AD: An Approach with Dual Feature Extraction Architecture and Dual Attention Mechanism for Image Anomaly Detection by Babak Masoudi

“…DFDA-AD consists of dual feature extraction from images by pre-trained DenseNet121 and ResNet50 networks. Two attention mechanisms are improved and developed in this paper, which provide more important feature maps for clustering by K-means algorithm. …”
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The Impact of Anatomic Racial Variations on Artificial Intelligence Analysis of Filipino Retinal Fundus Photographs Using an Image-Based Deep Learning Model by Carlo A. Kasala, MD, Kaye Lani Rea B. Locaylocay, MD-MBA, Paolo S. Silva, MD

“…Conclusions: The availability and sources of AI training datasets can introduce biases into AI algorithms. …”
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Policy-Based Reinforcement Learning Approach in Imperfect Information Card Game by Kamil Chrustowski, Piotr Duch

“…Moreover, leveraging the off-policy experience replay, along with the importance weighting of behavioural policy, enhanced training stability and reduced model variance. The proposed algorithm was applied to the trick-taking stage of the popular game Thousand Schnapsen in a two-player setup. …”
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On the generalisation capabilities of Fisher vector‐based face presentation attack detection by Lázaro J. González‐Soler, Marta Gomez‐Barrero, Christoph Busch

“…In contrast, for more realistic scenarios, existing algorithms face difficulties in detecting unknown PAI species which are only included in the test set. …”
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Deep Reinforcement Learning Object Tracking Based on Actor-Double Critic Network by Jing Xin, Jianglei Zhou, Xinhong Hei, Pengyu Yue, Jia Zhao

“…Aiming at the problem of poor tracking robustness caused by severe occlusion, deformation, and object rotation of deep learning object tracking algorithm in complex scenes, an improved deep reinforcement learning object tracking algorithm based on actor-double critic network is proposed. …”
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Literature review for the topic of automation of scheduling classes and exams in higher education institutions by Wadhah M Al-Gabri

“…These techniques and algorithms are compared from the standpoint of modern system-analysis methods. …”
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VMD‐FBCCA classification method for SSVEP brain–computer interfaces by Ping Tan, Fengsheng Wang, Kaijun Zhou, Yi Shen

“…To address this problem, a variational mode decomposition–based filter bank canonical correlation analysis (VMD‐FBCCA) algorithm is proposed, which integrates the adaptive characteristics of VMD and the training‐free nature of the FBCCA algorithm. …”
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Machine learning for predicting Chagas disease infection in rural areas of Brazil. by Fabio De Rose Ghilardi, Gabriel Silva, Thallyta Maria Vieira, Ariela Mota, Ana Luiza Bierrenbach, Renata Fiuza Damasceno, Lea Campos de Oliveira, Alexandre Dias Porto Chiavegatto Filho, Ester Sabino

“…We analyzed data from the Retrovirus Epidemiology Donor Study (REDS) to train five popular machine learning algorithms. The sample comprised 2,006 patients, divided into 75% for training and 25% for testing algorithm performance. …”
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Predicting the Attraction and Retention of Customers in Sports Pools in Isfahan City Using a Decision Tree: Presenting a Data Mining-Based Model by Seyed Masoud Mirsaeidi, Davood Nasr Esfahani

“…The purpose of this research is collective learning techniques and a combination of classification algorithms in data mining, evaluated the performance of these algorithms to predict whether customers of Isfahan sports pools would drop over a 6-year period. …”
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