Potential for artificial intelligence in medicine and its application to male infertility by Hideyuki Kobayashi

“…It would be ideal for physicians to acquire a knowledge of AI and even create AI models. No‐code AI tools have revolutionized model creation, allowing individuals to independently handle data preparation and model development. …”
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Towards cycle-to-cycle control: AI-based heat release rate prediction of a diesel engine operated in low temperature combustion mode by Márton Virt, Máté Zöldy

“…Therefore, this work aims to create AI models to predict combustion characteristics under varying conditions, including conventional and LTC operations. 113 different intake oxygen concentrations were set by exhaust gas recirculation, and the heat release rates and combustion pressures were predicted with neural networks. …”
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Interactive Mitigation of Biases in Machine Learning Models for Undergraduate Student Admissions by Kelly Van Busum, Shiaofen Fang

“…Because these issues are intrinsically subjective and context-dependent, creating trustworthy software requires human input and feedback. (1) Introduction: This work introduces an interactive method for mitigating the bias introduced by machine learning models by allowing the user to adjust bias and fairness metrics iteratively to make the model more fair in the context of undergraduate student admissions. (2) Related Work: The social implications of bias in AI systems used in education are nuanced and can affect university reputation and student retention rates motivating a need for the development of fair AI systems. (3) Methods and Dataset: Admissions data over six years from a large urban research university was used to create AI models to predict admissions decisions. These AI models were analyzed to detect biases they may carry with respect to three variables chosen to represent sensitive populations: gender, race, and first-generation college students. …”
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AI-Driven Surrogate Model for Room Ventilation by Jaume Luis-Gómez, Francisco Martínez, Alejandro González-Barberá, Javier Mascarós, Guillem Monrós-Andreu, Sergio Chiva, Elisa Borrás, Raúl Martínez-Cuenca

“…The presented results highlight the potential of this methodology to create AI-driven digital twins for the control of room ventilation.…”
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Analyzing K-12 AI education: A large language model study of classroom instruction on learning theories, pedagogy, tools, and AI literacy by Di Wu, Meng Chen, Xu Chen, Xing Liu

“…Specifically, integrating Project-based/Problem-based learning (PBL) with Collaborative learning appears effective in cultivating the capacity to evaluate and create AI.…”
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How helping students design ethical metaverse platforms can lead to safety and well being for all by Binod Sundararajan, Malavika Sundarararjan

“…The paper also offers a detailed review along with the pros and cons of several ethical frameworks and puts forth two key questions to students asking them to design a metaverse platform that can, a) ensure the wellbeing, security, and safety of the users who are not even aware that their minds may be swayed and manipulated; and b) find a way to convince companies that create AI-based metaverses to adopt ethical frameworks. …”
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Impact of Artificial Intelligence and Robotics on Early Childhood Education: A Framework-Based Approach Utilizing the Five Big Ideas Model by Basma Rashed Alghufali

“…This study investigates the proposed system which emphasizes the utilize of mechanical autonomy and play-based learning to create AI available and empower engagement among youthful children who have not begun formal tutoring. …”
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Is air pollution a risk factor for early menopause? by Joyce Mary Kim, Surabhi Shah, Jieun Min, Kyungah Jeong, Eun-Hee Ha

“…These data were linked with summary pollution data from AiMS-CREATE (AI-Machine Learning and Statistics Collaborative Research Ensemble for Air Pollution, Temperature, and All Types of Environmental Exposures) from 2002 to 2020. …”
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Artificial intelligence for modeling and understanding extreme weather and climate events by Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Adrian Höhl, Andrea Castelletti, Aytac Pacal, Claire Robin, Francesco Martinuzzi, Ioannis Papoutsis, Ioannis Prapas, Jorge Pérez-Aracil, Katja Weigel, Maria Gonzalez-Calabuig, Markus Reichstein, Martin Rabel, Matteo Giuliani, Miguel D. Mahecha, Oana-Iuliana Popescu, Oscar J. Pellicer-Valero, Said Ouala, Sancho Salcedo-Sanz, Sebastian Sippel, Spyros Kondylatos, Tamara Happé, Tristan Williams

“…We emphasize the need for collaboration across different fields to create AI solutions that are practical, understandable, and trustworthy to enhance disaster readiness and risk reduction.…”
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Machine learning for the diagnosis accuracy of bipolar disorder: a systematic review and meta-analysis by Yi Pan, Pushi Wang, Bowen Xue, Yanbin Liu, Xinhua Shen, Shiliang Wang, Xing Wang

“…With the growing utilization of artificial intelligence in mental health, researchers are endeavoring to create AI-based diagnostic models. In this context, some researchers have sought to develop machine learning models for bipolar disorder diagnosis. …”
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Analysis of AI Policy Guidelines at Taiwan’s Top Universities and Teaching Exploration at NCCU Libraries by Chun-Ru Ko

“…The revised program will emphasize AI literacy—encompassing understanding AI, using AI, evaluating AI, and creating AI—and introduce ethically responsible approaches to AI use in academic work. …”
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Navigating the AI landscape in SMEs: Overcoming internal challenges and external obstacles for effective integration. by Roziah Mohd Rasdi, Nordahlia Umar Baki

“…Ultimately, this research highlights the need of creating AI implementation plans that are customized to the distinct requirements and situations of SMEs. …”
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Machine Learning and Artificial Intelligence in the Food Industry: A Sustainable Approach by Rajnish Kler, Ghada Elkady, Kantilal Rane, Abha Singh, Md Shamim Hossain, Dheeraj Malhotra, Samrat Ray, Komal Kumar Bhatia

“…Various investigators created AI and ML-related models that were verified and found to be effective in optimising FI, and so the use of AI and ML in FI networks provides competitive advantages for improvement. …”
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A conceptual ethical framework to preserve natural human presence in the use of AI systems in education by Werner Alexander Isop

“…On the other hand, there is a risk that natural human presence may be gradually replaced by arbitrarily created AI systems, particularly due to their rapidly increasing yet partially unguided capabilities. …”
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AI-Driven Insect Detection, Real-Time Monitoring, and Population Forecasting in Greenhouses by Dimitrios Kapetas, Panagiotis Christakakis, Sofia Faliagka, Nikolaos Katsoulas, Eleftheria Maria Pechlivani

“…The main challenge is creating AI models that perform with speed and accuracy, enabling immediate farmer action. …”
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Artificial Intelligence in Dermatology: A Review of Methods, Clinical Applications, and Perspectives by Agnieszka M. Zbrzezny, Tomasz Krzywicki

“…This work aims to review current research, map applicable legal regulations, identify ethical challenges and methods of verifying AI models in dermatology, assess publication trends, compare the most popular neural network architectures and datasets, and identify good practices in creating AI-based applications for dermatological use. …”
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Personalized Clustering for Emotion Recognition Improvement by Laura Gutiérrez-Martín, Celia López-Ongil, Jose M. Lanza-Gutiérrez, Jose A. Miranda Calero

“…This customization requires several steps: creating clusters of subjects with similar behaviors, creating AI models for every cluster, continually updating these models with new data, and enrolling new subjects in clusters when required. …”
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Finite element analysis-assisted surgical planning and evaluation of flap design in hand surgery by Guang Yang, Hui Shen, Yewon Jang, Xiangyi Cheng

“…These include exploring techniques to unfold 3D wound surfaces into 2D representations, which can improve mesh quality and computational efficiency; validating FEA simulations through large-scale, multicenter clinical studies to ensure robustness and generalizability; developing real-time AR/MR systems that integrate simulation or optimization results into surgical workflows; and creating AI-powered platforms that learn from clinical data to provide adaptive and personalized flap design recommendations. …”
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Intelligent micro-electro-mechanical system for predictive nano-drug synthesis: Acousto-microfluidic heat and mass transportation by Afshin Kouhkord, Fariddodin Hassani, Ali Golshani, Reza Ansari

“…The outcomes and the intelligent framework presented here serve as a guide for creating AI-integrated micro-electro-mechanical devices, aiming controlled heat and mass transfer for precise nanoparticle synthesis. …”
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Data Confidentiality in Artificial Intelligence-Assisted Medicine: The Main Ethical Issue by Raluca DUMACHE, Camelia MURESAN, Marina Adriana MERCIONI, Alin IONESCU, Nina IVANOVIC, Alexandra ENACHE

“…Materials and Methods: The study entails gathering patient data from electronic health records (EHRs), anonymizing it, creating AI algorithms for recommending treatments and diagnosing diseases, putting strong security measures in place, abiding by ethical standards, identifying and reducing biases in AI algorithms, and making sure that laws like GDPR and HIPAA are followed. …”
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