Causal Relationships Between the Use of AI, Therapeutic Alliance, and Job Engagement Among Psychological Service Practitioners by Boshra A. Arnout, Sami M. Alshehri

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A dataset of annotated African plum images from Cameroon for AI-based quality assessmentKaggle by Arnaud Nguembang Fadja, Armel Gabin Fameni Tagni, Sain Rigobert Che, Marcellin Atemkeng

“…Potential applications include AI-based tools for real-time sorting, defect detection, and quality assurance in the supply chain.…”
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Interview with Marc Prensky on Digital Natives and AI Natives: Reframing and Empowering 21st Century Kids by Gülden Demir

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Exploring the typhoon intensity forecasting through integrating AI weather forecasting with regional numerical weather model by Hongxiong Xu, Yang Zhao, Zhao Dajun, Yihong Duan, Xiangde Xu

“…Abstract Recent advancements in artificial intelligence (AI) have notably enhanced global weather forecasting, yet accurately predicting typhoon intensity remains challenging. …”
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Measuring the Impact on Human Emotion When Listening and Reciting the Quran using AI/Machine Learning Techniques by Nur Asyiqin Hamzah, Hadhrami Ab Ghanni, Azlan Abd Aziz, Nur Hasanah Ali, Noor Zielah Abd Rahman

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From Serendipity to Precision: Integrating AI, Multi-Omics, and Human-Specific Models for Personalized Neuropsychiatric Care by Masaru Tanaka

Subjects: “…artificial intelligence (AI)…”
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Predicting Intensive Care Unit Admissions in COVID-19 Patients: An AI-Powered Machine Learning Model by A. M. Mutawa

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Exploring ethical considerations in medical research: Harnessing pre-generated transformers for AI-powered ethics discussions. by Takuya Mori, Takuya Watanabe, Shinji Kosugi

“…We requested the generative AI to provide insights on ethical considerations for virtual research involving individuals. …”
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AutoMEX: Streamlining material extrusion with AI agents powered by large language models and knowledge graphs by Haolin Fan, Junlin Huang, Jilong Xu, Yifei Zhou, Jerry Ying Hsi Fuh, Wen Feng Lu, Bingbing Li

“…We propose AutoMEX, an innovative framework that integrates large language models (LLMs) as artificial intelligence (AI) agents to automate the MEX process to address these limitations. …”
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Sustainable materials for artificial intelligence (AI) technology adoption for energy-efficient patient-centric healthcare solutions by Lakshmipriya Bachina, Anusha Kanagala, Sattibabu Korapu, P Ratnaraju

Subjects: “…artificial intelligence (ai)…”
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Dai liquori casalinghi ai liquori della tradizione: il caso delle Valli di Lanzo by Gianpaolo Fassino

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Author Correction: Establishing responsible use of AI guidelines: a comprehensive case study for healthcare institutions by Agustina D. Saenz, Mass General Brigham AI Governance Committee, Amanda Centi, David Ting, Jacqueline G. You, Adam Landman, Rebecca G. Mishuris

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AI Machine Learning–Based Diabetes Prediction in Older Adults in South Korea: Cross-Sectional Analysis by Hocheol Lee, Myung-Bae Park, Young-Joo Won

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Automated AI-based image analysis for quantification and prediction of interstitial lung disease in systemic sclerosis patients by Julien Guiot, Monique Henket, Fanny Gester, Béatrice André, Benoit Ernst, Anne-Noelle Frix, Dirk Smeets, Simon Van Eyndhoven, Katerina Antoniou, Lennart Conemans, Janine Gote-Schniering, Hans Slabbynck, Michael Kreuter, Jacobo Sellares, Ioannis Tomos, Guang Yang, Clio Ribbens, Renaud Louis, Vincent Cottin, Sara Tomassetti, Vanessa Smith, Simon L. F. Walsh

“…We used a retrospective cohort of 75 SSc-ILD patients to evaluate the potential of the AI-based quantification tool and to correlate image-based quantification with pulmonary function tests and their evolution over time. …”
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“Scarlet Cloak and the Forest Adventure”: a preliminary study of the impact of AI on commonly used writing tools by Barbara Bordalejo, Davide Pafumi, Frank Onuh, A. K. M. Iftekhar Khalid, Morgan Slayde Pearce, Daniel Paul O’Donnell

“…Abstract This paper explores the growing complexity of detecting and differentiating generative AI from other AI interventions. Initially prompted by noticing how tools like Grammarly were being flagged by AI detection software, it examines how these popular tools such as Grammarly, EditPad, Writefull, and AI models such as ChatGPT and Microsoft Bing Copilot affect human-generated texts and how accurately current AI-detection systems, including Turnitin and GPTZero, can assess texts for use of these tools. …”
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Development and validation of a novel AI-derived index for predicting COPD medical costs in clinical practice by Guan-Heng Liu, Chin-Ling Li, Chih-Yuan Yang, Shih-Feng Liu

“…This study developed and validated an AI-driven COPD Medical Cost Prediction Index (MCPI) to forecast healthcare expenses in COPD patients. …”
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iDIA-QC: AI-empowered data-independent acquisition mass spectrometry-based quality control by Huanhuan Gao, Yi Zhu, Dongxue Wang, Zongxiang Nie, He Wang, Guibin Wang, Shuang Liang, Yuting Xie, Yingying Sun, Wenhao Jiang, Zhen Dong, Liqin Qian, Xufei Wang, Mengdi Liang, Min Chen, Houqi Fang, Qiufang Zeng, Jiao Tian, Zeyu Sun, Juan Xue, Shan Li, Chen Chen, Xiang Liu, Xiaolei Lyu, Zhenchang Guo, Yingzi Qi, Ruoyu Wu, Xiaoxian Du, Tingde Tong, Fengchun Kong, Liming Han, Minghui Wang, Yang Zhao, Xinhua Dai, Fuchu He, Tiannan Guo

“…We then prioritize 15 metrics and invite 21 experts to manually assess the quality of 2754 DIA files based on those metrics. We develop an AI model for DIA-based QC using 2110 training files. …”
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AI-Driven Meat Food Drying Time Prediction for Resource Optimization and Production Planning in Smart Manufacturing by Rajnish Rakholia, Andres L. Suarez-Cetrulo, Manokamna Singh, Ricardo Simon Carbajo

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A pedagogical approach: toward leveraging mathematical modeling and AI to support integrating humanities into STEM education by Quintana M. Clark

“…This paper examines the transformative potential of integrating humanities into STEM education using interdisciplinary approaches, AI, and Model Eliciting Activities (MEAs). The integration is motivated by the increasing complexity of global challenges, such as climate change, which demand solutions that extend beyond traditional STEM boundaries and incorporate ethical, cultural, and societal considerations. …”
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Correction of CAMS PM₁₀ Reanalysis Improves AI-Based Dust Event Forecast by Ron Sarafian, Sagi Nathan, Dori Nissenbaum, Salman Khan, Yinon Rudich

“…Comparing the network’s performance when trained on both original and bias-corrected CAMS PM₁₀ fields, we show that the correction improves AI-based forecasting performance across all metrics.…”
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