An in vivo microscopy dataset for the characterization of leukocyte death by Alain Pulfer, Diego Ulisse Pizzagalli, Miguel Palomino Segura, Nina Germic, Tommaso Virgilio, Mauro Di Pilato, Pau Carrillo Barbera, Elisa Palladino, Paola Antonello, Marcus Thelen, Hans-Uwe Simon, Rolf Krause, Santiago F. Gonzalez

“…However, the limited throughput of this technology, together with a lack of openly accessible datasets, affects the development of algorithms for the automatic detection and characterization of cell death, which in turn require the integration of extensive and curated datasets. …”
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The Role of Artificial Intelligence in Criminal Investigations in India by Kumar Navin

“…However, this use of AI in Criminal Investigation also raises concerns, particularly in the space of privacy and surveillance, protection of data and algorithmic bias. More specifically, the country’s regulatory framework for the use of AI by law enforcement agencies is extremely weak and underdeveloped, which opens the door to abuse and the infringement of certain fundamental rights. …”
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ARTIFICIAL INTELLIGENCE AS AN OBJECT OF MANAGEMENT: A BENEFIT FOR CIVILISATION OR A THREAT TO MANKIND? by Iia Chudayeva, Boris Dmitruk

“…The authors of the article analyze the reasons for the rapid development and implementation of artificial intelligence achievements, which opens up great opportunities for solving problems in many industries and is a reliable assistant to people in everyday life. …”
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Artificial intelligence driven innovations in biochemistry: A review of emerging research frontiers by Mohammed Abdul Lateef Junaid

“…Key AI techniques—such as machine learning algorithms, natural language processing, and AI-based molecular modeling—are discussed. …”
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Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models. by Zenglei Liu, Ailian Gao, Hui Sheng, Xueling Wang

“…An evaluation of the suggested method was carried out by comparison experiments between state-of-the-art algorithms and the proposed methodology. Empirical findings demonstrate that the suggested methodology surpasses the most advanced algorithms on the datasets that are accessible openly. …”
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Insight Thoughts for Intelligent Traffic Management-Based SDN by Sara Sadiq Jawad, Dheyaa Jasim Kadhim, Yusmadi Yah Bt Jusoh

“…This paper introduces the integration of AI algorithms into the SDN controller so that you can make intelligent decisions using predictive analytics of future traffic, what it requires, and network capacity requirements. …”
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Hybrid Machine Learning in Hydrological Runoff Forecasting: An Exploration of Extreme Gradient-Boosting and Categorical Gradient Boosting Optimization in the Russian River Basin by Reza Seifi Majdar, Ali Rahnamaei, Vahid Babazadeh

“…Recent advances in machine learning (ML) have opened new opportunities to improve prediction accuracy. …”
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Diagnostic Analysis of Crosswalk Safety Hazards in Pedestrian Environments: A SHAP-Enhanced Machine Learning Approach With Street-View Imagery by Caryl Anne M. Barquilla, Jeongwoo Lee

“…A lower sky openness ratio combined with a higher building ratio was associated with increased crash likelihood, whereas greater sidewalk coverage and the presence of traffic control measures, including traffic lights and crosswalk time indicators, mitigated risk. …”
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Construction and SHAP interpretability analysis of a risk prediction model for feeding intolerance in preterm newborns based on machine learning by Hui Xu, Xingwang Peng, Ziyu Peng, Rui Wang, Rui Zhou, Lianguo Fu

“…When feeding, early milk opening, the use of probiotics, the stimulation of defecation and other measures should be implemented with the aim of reducing the occurrence of FI.…”
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Renji endoscopic submucosal dissection video data set for colorectal neoplastic lesions by Jinnan Chen, Xiangning Zhang, Jinneng Wang, Tang Cao, Chunjiang Gu, Zhao Li, Yiming Song, Liuyi Yang, Zhengjie Zhang, Qingwei Zhang, Dahong Qian, Xiaobo Li

“…Recognition systems for endoscopic surgical phases using deep learning algorithms heavily rely on comprehensive annotated datasets. …”
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Duty of care, data science, and gambling harm: A scoping review of risk assessment models by Virve Marionneau, Kim Ristolainen, Tomi Roukka

“…Online operators often employ risk detection algorithms to accomplish this task. This scoping review focuses on how such data science applications can perform from a duty of care perspective. …”
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Modification of Adomian decomposition technique in multiplicative calculus and application for nonlinear equations by Farooq Ahmed Shah, Muhammad Waseem, Alexey Mikhaylov, Gabor Pinter

“…The purpose in constructing new algorithms is to show the implementation and effectiveness of multiplicative calculus.…”
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Enhancing Mobile App Recommendations With Crowdsourced Educational Data Using Machine Learning and Deep Learning by Naadiya Mirbahar, Kamlesh Kumar, Asif Ali Laghari

“…Mobile devices make it easier to gather educational data through crowdsourcing, which opens new possibilities for improving app recommendation algorithms. …”
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Cracking Process of Early-Age Concretes: Basis of Numerical Probabilistic Models by Pierre Rossi

“…Additionally, it outlines specific algorithmic development approaches tailored to each model. …”
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An intrusion detection method based on system call sequence for train-mounted host devices by WANG Xue, WANG Lide, WANG Biao, XU Shuxian, WANG Chong

“…With the increasing compatibility and openness of the train communication network, there is a risk of cyberattacks on the train-mounted host devices. …”
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Assessing the Current Limitations of Large Language Models in Advancing Health Care Education by JaeYong Kim, Bathri Narayan Vajravelu

“…Future research should focus on strategically addressing the persistent challenges of LLMs highlighted in this paper, opening the door for effective measures that can improve their application in health care education.…”
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Groundwater Level Forecasting Using Machine Learning: A Case Study of the Baekje Weir in Four Major Rivers Project, South Korea by Sooyeon Yi, G. Mathias Kondolf, Samuel Sandoval Solis, Larry Dale

“…The study utilizes observed data that simulates conditions with and without the weir, including scenarios of full gate opening. Multiple machine learning algorithms—Random Forest (RF), Artificial Neural Network, Support Vector Regression (SVR), Gradient Boosting, and Extreme Gradient Boosting (XGBoost)—are used to develop accurate groundwater level prediction models. …”
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SHRiMP: accurate mapping of short color-space reads. by Stephen M Rumble, Phil Lacroute, Adrian V Dalca, Marc Fiume, Arend Sidow, Michael Brudno

“…The development of Next Generation Sequencing technologies, capable of sequencing hundreds of millions of short reads (25-70 bp each) in a single run, is opening the door to population genomic studies of non-model species. …”
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A STUDY OF PEOPLE’S PERCEPTION OF ARTIFICIAL INTELLIGENCE IN FINANCE AND SOCIETY by Dan MITRA, Ioana-Florina COITA

“…Some of the key issues included algorithmic bias, erosion of human oversight, and threats to privacy. …”
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Gravity Predictions in Data-Missing Areas Using Machine Learning Methods by Yubin Liu, Yi Zhang, Qipei Pang, Sulan Liu, Shaobo Li, Xuguo Shi, Shaofeng Bian, Yunlong Wu

“…In recent years, the rapid development of artificial intelligence has opened up a new opportunity for data prediction. In this study, utilizing the EGM2008 satellite gravity model, we conducted a comprehensive analysis of three machine learning algorithms—random forest, support vector machine, and recurrent neural network—and compared their performances against the traditional Kriging interpolation method. …”
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