Unraveling Algerian bat coronaviruses: from initial detection to genome recovery and co-infection discovery by Dr Safia Zeghbib, Zsófia Tauber, Dr Tamás Görföl, Karimane Malek Zeghbib, Dr Mourad Ahmim, Dr Gábor Kemenesi

“…Methods: A total of 97 bat guano samples were collected from three caves in urban areas of Algeria. …”
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Use of Saliva Analytes as a Predictive Model to Detect Diseases in the Pig: A Pilot Study by Eva Llamas-Amor, Alba Ortín-Bustillo, María José López-Martínez, Alberto Muñoz-Prieto, Edgar García Manzanilla, Julián Arense, Aida Miralles-Chorro, Pablo Fuentes, Silvia Martínez-Subiela, Antonio González-Bulnes, Elena Goyena, Andrea Martínez-Martínez, José Joaquín Cerón, Fernando Tecles

“…Background/Objectives: Saliva is gaining importance as a diagnostic sample in pigs. The aim of this research was to evaluate a panel of salivary analytes in three porcine diseases and establish predictive models to detect them. …”
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Detection of Blood Protozoa Infecting Broiler Chicken Farms in Tanjung Gunung Village, District Jombang by Marchelia Arifiandani, Endang Suprihati, Wiwik Misaco Yuniarti, Nunuk Dyah Retno Lastuti, Poedji Hastutiek, Sunaryo Hadi Warsito

“…The main purpose of this researchis to detect Leucocytozoonosis and Plasmodiosis infections on broiler farms in Tnjung Gunung Village, District Jombang using 50 broiler chickens by Purposive Sampling  of 2 bredeers. …”
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Sensitivity of field tests, serological and molecular techniques for Plum Pox Virus detection in various tissues by Mojca VIRŠČEK MARN, Irena MAVRIČ PLEŠKO, Denise ALTENBACH, Walter BITTERLIN

“…PPV was detected only in some of the samples of asymptomatic parts of the leaves with symptoms and of stalks by field tests and DAS-ELISA. …”
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A Hybrid Method of 1D-CNN and Machine Learning Algorithms for Breast Cancer Detection by Ahmed Adil Nafea, Manar AL-Mahdawi, Khattab M Ali Alheeti, Mustafa S. Ibrahim Alsumaidaie, Mohammed M AL-Ani

“…However, there are some limitations regarding accuracy in detection. This study introduces an approach that utilizes 1D CNN as feature extraction and employs machine learning (ML) algorithms such as XGBoost, random forests (RF), decision trees (DT) support vector machines (SVM) and k nearest neighbor (KNN) to classify samples as either benign or malignant aiming to enhance accuracy. …”
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Cancer phylogenetic inference using copy number alterations detected from DNA sequencing data by Bingxin Lu

“…Many phylogenetic inference methods using CNAs detected from bulk or single-cell DNA sequencing data have been developed over the years. …”
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The data dimensionality reduction and bad data detection in the process of smart grid reconstruction through machine learning. by Bo Yu, Zheng Wang, Shangke Liu, Xiaomin Liu, Ruixin Gou

“…When the number of iTree n is determined to be 100, and the corresponding number of samples w is determined to be 10, the algorithm has the best detection effect. …”
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A precise machine learning model: Detecting cervical cancer using feature selection and explainable AI by Rashiduzzaman Shakil, Sadia Islam, Bonna Akter

“…In addition, two data balancing techniques—Synthetic Minority Oversampling Technique and Adaptive Synthetic Sampling—were used to mitigate the data imbalance issues. …”
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Oversampling and undersampling for intrusion detection system in the supervisory control and data acquisition IEC 60870‐5‐104 by M. Agus Syamsul Arifin, Deris Stiawan, Bhakti Yudho Suprapto, Susanto Susanto, Tasmi Salim, Mohd Yazid Idris, Rahmat Budiarto

“…Experimental results indicate that the intrusion detection system model using decision tree and random forest classifiers using random under‐sampling achieved the highest accuracy of 99.05%. …”
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Artificial intelligence as the clinical assistant for detection of femoral neck fracture: Intelligent medicine brings the bright future by Pengran Liu, Dan Zhang, Yufei Chen, Ying Fang, Jiayao Zhang, Honglin Wang, Jialang Hu, Binlei Sun, Rui Jiao, Jiaming Yang, Yi Xie, Mingdi Xue, Hong Zhou, Zhewei Ye

“…And the performance of AI-aided human level is also explored to confirm the value of AI as an assistant for clinical doctors to detect the FNF. Materials and methods: 4477 hip X-rays (consisted of 2884 FNF X-rays and 1593 normal hip X-rays) from eight Chinese top tree hospitals (Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (Wuhan Union Hospital), Wuhan Pu'ai Hospital, Tianyou Hospital, Wuhan University of Science and Technology, Hanyang Hospital, Wuhan University of Science and Technology, Northern Jiangsu People's Hospital, Xiangya Changde Hospital, People's Hospital of Tibet Autonomous Region and the Second Affiliated Hospital of Soochow University) were collected to establish a large multi-center clinical sample database. …”
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Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm by Wenliang Zhu, Guanming Qiu

“…Secondly, by merging collision detection with Kalman filtering, and by comparing the step sizes between newly generated child nodes and random tree nodes towards the root node, we filtered redundant points from the path, thereby reducing the count of effective points and optimizing the path. …”
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Data-Driven Fault Detection and Diagnosis in Cooling Units Using Sensor-Based Machine Learning Classification by Amilcar Quispe-Astorga, Roger Jesus Coaquira-Castillo, L. Walter Utrilla Mego, Julio Cesar Herrera-Levano, Yesenia Concha-Ramos, Erwin J. Sacoto-Cabrera, Edison Moreno-Cardenas

“…A database with 20,000 samples was obtained, which includes normal and failed operating events generated in the PAC. …”
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Advances in Corneal Diagnostics Using Machine Learning by Noor T. Al-Sharify, Salman Yussof, Nebras H. Ghaeb, Zainab T. Al-Sharify, Husam Yahya Naser, Sura M. Ahmed, Ong Hang See, Leong Yeng Weng

“…The Decision Tree achieved classification accuracy of 62% for training and 65.7% for testing, while Nearest Neighbor Analysis yielded 65.4% for training and 62.6% for holdout samples. …”
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3D Pulse Image Detection and Pulse Pattern Recognition Based on Subtle Motion Magnification Technology by Chongyang YAO, Yongxin CHOU, Zhiwei LIANG, Haiping YANG, Jicheng LIU, Dongmei LIN

“…On this basis, nine features are extracted from the 3D pulse signals and features selection is performed using a two-sample Kolmogorov-Smirnov test. Finally, machine learning algorithms such as decision trees and random forests are used to identify the five types of pulse conditions: deep pulse, intermittent pulse, flooding pulse, slippery pulse, and rapid pulse. …”
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DNA barcoding of Culicoides biting midges (Diptera: Ceratopogonidae) and detection of Leishmania and other trypanosomatids in southern Thailand by Piyapat Tepboonrueng, Thanapat Pataradool, Rungfar Boonserm, Luke W. Rimmer, Kanok Preativatanyou, Sakone Sunantaraporn, Padet Siriyasatien

“…In contrast, L. orientalis was detected in Sichon district, Nakhon Si Thammarat province. …”
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Enhancing credit card fraud detection: the impact of oversampling rates and ensemble methods with diverse feature selection by Mohamed Akouhar, Abdallah Abarda, Mohamed El Fatini, Mohamed Ouhssini

“…The subject matter of this article is enhancing credit card fraud detection systems by exploring the impact of oversampling rates and ensemble methods with diverse feature selection techniques. …”
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AI-based orchard monitoring at night: Enhancing sustainable fruit production through real-time apple detection by Kutyrev Alexey, Khort Dmitry, Smirnov Igor, Zubina Valeria

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A Dual-Strategy Framework for Cyber Threat Detection in Imbalanced, High-Dimensional Data Across Heterogeneous Networks by T. Saranya, S. Indra Priyadharshini

“…First, the Variance Split Adaptive Sampling KD-SMOTE (VAST-KD-SMOTE) technique addresses data imbalance by strategically under-sampling majority class instances using a variance-based KD-Tree. …”
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Detection and Whole Genome Amplification of the 4d Type of Porcine Hepatitis E Virus in Eastern Tibet, China by Yongzhi Lou, Jiaojiao Xin, Sizhu Suolang, Da Qiong, Zhuoma Dawa, Ga Gong

“…No tissue samples tested positive for the virus. Cloned sequences were uploaded to GenBank (accession numbers: OR392679‐OR392685, OR355817‐OR355824 and OR909495‐OR909502) and a phylogenetic tree constructed. …”
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An ultrasonic-AI hybrid approach for predicting void defects in concrete-filled steel tubes via enhanced XGBoost with Bayesian optimization by Shuai Wan, Shipan Li, Zheng Chen, Yunchao Tang

“…Based on 3600 ultrasonic measurement samples, an Extreme Gradient Boosting (XGBoost) model was enhanced through oversampling and hyperparameter optimization via Bayesian optimization (BO-XGBoost). …”
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