Evaluating the feasibility of automating dataset retrieval for biodiversity monitoring by Alexandre Fuster-Calvo, Sarah Valentin, William C. Tamayo, Dominique Gravel

“…Automating these tasks through advanced algorithms holds immense potential to revolutionize biodiversity monitoring. …”
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Neurological adverse events associated with baclofen: a pharmacovigilance study based on FDA adverse event reporting system by Yunhan Zhao, Haoxiang Hu, Jiesheng Mao, Jianghai He, Yihan Zhang, Xiaokai Yang

“…These methods were used to detect and evaluate adverse events Adverse drug events associated with baclofen. …”
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Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

“…Most Reinforcement Learning (RL) algorithms optimize a single-objective function, whereas real-world decision-making involves multiple aspects. …”
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Sentiment analysis for deepfake X posts using novel transfer learning based word embedding and hybrid LGR approach by Madiha Khalid, Muhammad Faheem Mushtaq, Urooj Akram, Mejdl Safran, Sultan Alfarhood, Imran Ashraf

“…In this study, we compare the proposed approach with a range of machine learning algorithms, as well as, DL techniques for validation. …”
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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…As part of this study, we compared the outputs generated by two unsupervised machine learning algorithms with a conventional image clustering technique. …”
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Advances in the application of nomograms for patients with gastric cancer associated with peritoneal metastasis by Shiyang Jin, Zeshen Wang, Qiancheng Wang, Zhenglong Li, Xirui Liu, Kuan Wang

“…Imaging-based models leverage CT radiomics and deep learning algorithms to detect occult PM, with Huang et al.’s deep learning model attaining an AUC of 0.900. …”
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Machine Learning Techniques for Kinship Verification: A Review by Olivia Oraha, Yusra Mohammad

“…Thus, with the progress of years the kinship verification entered the computer vision world to determining the relationships using machine learning (ML) algorithms such as deep learning, transfer learning techniques and others. …”
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Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

“… Human intervention cannot halt natural disasters like earthquakes, but machine learning application expertise can be utilized to detect patterns in data and increase understanding and predictive power. …”
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Utilizing MV-FLOW™ and multidimensional ultrasound characteristics for prognosticating FET outcomes in RIF patients: Study Protocol for a cross-sectional study. by Ying Zhou, Li-Ying Liu, Hua-Ju Yang, Yuan-Yuan Lai, Di Gan, Jie Yang

“…Based on the above, this study aims to establish and validate a clinical prediction model for FET outcomes using support vector classification (SVC) algorithms, based on MV-FLOW™ and multidimensional transvaginal ultrasound imaging features. …”
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Dual-verified secure localization method for unmanned intelligent vehicles by GU Xiaodan, XIA Guozheng, SONG Bingchen, YANG Ming, LUO Junzhou

“…Once an abnormal position was detected, an alert would be issued, ensuring the normal operation of the unmanned intelligent vehicles. …”
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Artificial intelligence as one of the key drivers of the economy digital transformation by O.I. Pizhuk

“…The prospects for using AI are huge as the algorithms that allow massive amounts of information to be processed on an hourly basis can detect cause-and-effect relationships, which are not achievable for a person, and thus make predictions more accurate and make solutions more efficient. …”
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The role of autofluorescence bronchoscopy in monitoring a tumorous lesion in the bronchial mucosa: a case report by Škrbić Dušan, Stojanović Goran, Považan Đorđe, Đurić Mirna, Eri Živka

“…Autofluorescence bronchoscopy (AFB) is a diagnostic procedure that is included in all diagnostic algorithms discovering precancerous lesions in the large airways. …”
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Early Warning Systems for Plant Diseases in delta regions: Machine Learning Approaches by Biswas Debarghya, Sharma Priti

“…Nevertheless, these are also sensitive to plant diseases because of the special environmental conditions like high humidity and frequence waterlogging. It is important to detect plant diseases early and manage to prevent substantial losses of crop and food security. …”
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Early identification of children with Attention-Deficit/Hyperactivity Disorder (ADHD). by Yang S Liu, Fernanda Talarico, Dan Metes, Yipeng Song, Mengzhe Wang, Lawrence Kiyang, Dori Wearmouth, Shelly Vik, Yifeng Wei, Yanbo Zhang, Jake Hayward, Ghalib Ahmed, Ashley Gaskin, Russell Greiner, Andrew Greenshaw, Alex Alexander, Magdalena Janus, Bo Cao

“…Our findings suggest that machine learning algorithms that use population-level surveillance data could be a valuable tool for early identification of ADHD.…”
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A model for maxilloturbinate morphogenesis in seals. by Jonathan E Kings, Lars P Folkow, Øyvind Hammer, Signe Kjelstrup, Matthew J Mason, Fengzhu Xiong, Eirik G Flekkøy

“…Here we report a model of maxilloturbinate pattern formation in prenatal and juvenile seals based on a simple algorithmic description and three key parameters: target turbinate porosity, characteristic ossification time scale, and typical gestation time scale. …”
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Using explainable machine learning and eye-tracking for diagnosing autism spectrum and developmental language disorders in social attention tasks by Adoración Antolí, Adoración Antolí, Francisco Javier Rodriguez-Lozano, José Juan Cañas, Julia Vacas, Julia Vacas, Fátima Cuadrado, Fátima Cuadrado, Araceli Sánchez-Raya, Araceli Sánchez-Raya, Carolina Pérez-Dueñas, Carolina Pérez-Dueñas, Juan Carlos Gámez-Granados

“…BackgroundEye-tracking technology has proven to be a valuable tool in detecting visual scanning patterns associated with autism spectrum disorder (ASD). …”
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ARAN: Age-Restricted Anonymized Dataset of Children Images and Body Measurements by Hezha H. MohammedKhan, Cascha Van Wanrooij, Eric O. Postma, Çiçek Güven, Marleen Balvert, Heersh Raof Saeed, Chenar Omer Ali Al Jaf

“…To create a suitable reference, we trained state-of-the-art deep learning algorithms on the ARAN dataset to predict body measurements from the images. …”
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Validation of 12 years (2008–2019) of IASI-A CO with IAGOS aircraft observations by B. Barret, P. Loicq, E. Le Flochmoën, Y. Bennouna, J. Hadji-Lazaro, D. Hurtmans, B. Sauvage

“…This global TCC agreement between the algorithms hides significant vertical and geographical differences. …”
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Adverse drug events (ADEs) risk signal mining related to eculizumab based on the FARES database by Xi-Feng Wang, Lu-Ri Bao, Ta-La Hu, Rui-Feng Xu, Wu-Niri Gao, Jing-Yuan Wang, Jian-Rong Zhao, Zhen-Li Fu, Shu-Fang Wang, Yan Meng

“…A total of 461 PTs were identified as satisfying by all four algorithms. These PTs reported adverse reactions consistent with the specifications, such as fatigue, nasopharyngitis, meningococcal infection, fever, and anemia. …”
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MACHINE LEARNING MODELS FOR PERFORMANCE PREDICTION OF YOUNG PLAYERS IN FOOTBALL ACADEMIES – A REVIEW by Armand Florin Bertea, Cezar Honceriu

“…The paper summarizes the different methods of using machine learning algorithms to detect new football talents, based on criteria such as physical, mental and technical qualities.…”
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