The classification method of donkey breeds based on SNPs data and machine learning by Dekui Li, Dekui Li, Xiaolong Hu, Yongdong Peng

“…For instance, chromosome Chr2 showed the highest classification accuracy with KNN, while chromosome Chr19 performed best with SVM and RF models. …”
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Artificial intelligence in soil science: Where do we go now? by Jose Pablo Castro, Caley K. Gasch, Paulo Flores

“…Abstract Recognizing the fast advancement of artificial intelligence (AI) in soil science, the main objective of this commentary paper is to discuss how this technology is being incorporated into the discipline, focusing on the most common algorithms and their applications. Employing a discursive and reflective methodology, the article draws insights from the authors' expertise and opinions. …”
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Facial Skin Analysis in Malaysians using YOLOv5: A Deep Learning Perspective by Ying Huey Gan, Shih Yin Ooi, Ying Han Pang, Yi Hong Tay, Quan Fong Yeo

“…The beauty sector market is increasing, and more skin type readers are being created to help people determine their skin type. While various skin type readers are in the market, each is invented and tested abroad. …”
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A Review of Non-Fully Supervised Deep Learning for Medical Image Segmentation by Xinyue Zhang, Jianfeng Wang, Jinqiao Wei, Xinyu Yuan, Ming Wu

“…We delve into the theoretical foundations, core advantages, typical application scenarios, and representative algorithmic implementations associated with each paradigm. …”
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E-scooter crash severity in the United Kingdom: A comparative analysis using machine learning techniques and random parameters logit with heterogeneity in means and variances by Ali Agheli, Kayvan Aghabayk, Matin Sadeghi, Subasish Das

“…We employed a random parameters logit model and investigated several machine learning algorithms, with XGBoost performing best. Analysis reveals that severe injuries are more likely in crashes involving senior riders, at night with lighting, and at T, staggered, or crossroad junctions. …”
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Impact of Public Space in Primary and Secondary Schools Based on Natural Visibility Ratio by Feng Liu, Hao Zhou, Jiangtao Xie, Yue Tang, Shuyu Liu

“…This study utilizes algorithmic simulations, spatial analysis, and statistical methods to examine the relationships between the layouts of buildings, public space morphology, and campus safety. …”
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A Study on a Variable-Gain PID Control for a Pneumatic Servo System Using an Optimized PSO-Type Neural Network by Shenglin Mu, Satoru Shibata, Daisuke Baba, Rikuto Oshita

“…The OPSO-type NNs are particularly efficient in solving complex optimization problems without requiring differential information, demonstrating superior simplicity and efficacy compared to traditional methods, such as genetic algorithms. In our approach, one of the OPSO-type NNs is utilized to tune the PID controller gains, while the other adjusts the control output. …”
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Simultaneous Instance and Attribute Selection for Noise Filtering by Yenny Villuendas-Rey, Claudia C. Tusell-Rey, Oscar Camacho-Nieto

“…Removing or reducing noise can help classification algorithms focus on relevant patterns, preventing them from being affected by irrelevant or incorrect information. …”
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Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction by Yang Yue, Shu Li, Yihua Cheng, Lie Wang, Tingjun Hou, Zexuan Zhu, Shan He

“…While most existing algorithms represent PPI complex graph structures at the atom-scale or residue-scale, these representations can be computationally expensive or may not sufficiently integrate finer chemical-plausible interaction details for improving predictions. …”
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Time-Series Forecasting for Peak Hour Traffic Accidents by Md. Ferdousul Haque Shikder, Yili Tang, Majid Emami Javanmard

“…The results provide references and practical insights into the potential of leveraging advanced algorithms and techniques to tackle the dynamics of traffic accidents and improve road safety.…”
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Improved Key Microbial Biomarker Discovery Using Ensemble Statistical Methods by Walter Pirovano, Yashjit Gangopadhyay, Mirna Lilian Baak, Christiaan Arie de Leeuw, Radhika Bongoni, Eline Suzanne Klaassens

“…However, advanced biostatistical analysis is required to properly combine microbiome taxonomic abundance data with phenotypical metadata and reliably predict disease states. While differential abundance analysis and machine-learning techniques are widely used to perform such analyses, selecting the best method is not trivial due to the complexity and specific characteristics of both the data and the algorithms. …”
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Comparing the Performance of Regression and Machine Learning Models in Predicting the Usable Area of Houses with Multi-Pitched Roofs by Leszek Dawid, Anna Marta Barańska, Paweł Baran

“…To address this problem, a study was conducted that used linear models, non-linear models and machine learning algorithms to calculate the floor area of buildings with complex multi-pitched roofs. …”
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Prediction of Graduate Career Relevance Based on Academic and Non-Academic Aspects using Machine Learning by Muhammad Yusuf Luthfi Ijlal, Arif Setiawan, Diana Laily Fithri

“…Three classification algorithms were applied: Decision Tree, Random Forest, and Support Vector Machine (SVM). …”
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Gene expression-based modeling of overall survival in Black or African American patients with lung adenocarcinoma by Bin Zhu, Stephanie S. McHale, Michelle Van Scoyk, Gregory Riddick, Pei-Ying Wu, Chu-Fang Chou, Ching-Yi Chen, Robert A. Winn

“…Unsupervised machine learning algorithms stratified B/AA patients into groups with distinct survival outcomes, while supervised algorithms demonstrated a higher accuracy in predicting survival for B/AA LUAD patients compared to white patients.DiscussionIn total, this study explored OS-associated genes and pathways specific for B/AA LUAD patients. …”
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Enhancing Automated Maneuvering Decisions in UCAV Air Combat Games Using Homotopy-Based Reinforcement Learning by Yiwen Zhu, Yuan Zheng, Wenya Wei, Zhou Fang

“…However, relying solely on the terminal outcome of victory or defeat as the optimization target, but without incorporating additional rewards throughout the process, poses significant challenges for reinforcement learning due to the sparse reward structure inherent in these scenarios. While algorithms enhanced with densely distributed artificial rewards show potential, they risk deviating from the primary objectives. …”
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Current application of artificial intelligence in laparoscopic cholecystectomy by S.M. Chooklin, S.S. Chuklin

“…Advances in AI have made it possible to train algorithms that identify anatomy and interpret the surgical field. …”
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Comparing bioinformatic pipelines for microbial 16S rRNA amplicon sequencing. by Andrei Prodan, Valentina Tremaroli, Harald Brolin, Aeilko H Zwinderman, Max Nieuwdorp, Evgeni Levin

“…However, specialized software and algorithms are needed to convert raw sequencing data into biologically meaningful information (i.e. tables of bacterial counts). …”
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Nonintrusive Load Disaggregation Based on Attention Neural Networks by Shunfu Lin, Jiayu Yang, Yi Li, Yunwei Shen, Fangxing Li, Xiaoyan Bian, Dongdong Li

“…House1 and House5 are employed as the training set, while House2 data is reserved for testing. The proposed model achieves lower errors for all appliances compared to other algorithms. …”
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Supervised Learning-Based Fault Classification in Industrial Rotating Equipment Using Multi-Sensor Data by Aziz Kubilay Ovacıklı, Mert Yagcioglu, Sevgi Demircioglu, Tugberk Kocatekin, Sibel Birtane

“…The performance of general machine learning algorithms such as kNN, SVM, RF, and some boosting techniques was evaluated, and it was shown that the Random Forest achieved the best classification accuracy. …”
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AI-Driven Wearable Bioelectronics in Digital Healthcare by Guangqi Huang, Xiaofeng Chen, Caizhi Liao

“…However, their widespread adoption faces technical, ethical, and regulatory hurdles, such as data interoperability, privacy concerns, algorithmic bias, and the need for robust clinical validation. …”
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