Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review by Amelia Surdu, Dana Gabriela Budala, Ionut Luchian, Liliana Georgeta Foia, Gina Eosefina Botnariu, Monica Mihaela Scutariu

“…AI technologies, such as machine learning, deep learning, and computer vision, are increasingly being integrated into dental practice to analyze clinical images, identify pathological conditions, and predict disease progression. By utilizing AI algorithms, dental professionals can detect issues like caries, periodontal disease and oral cancer at an earlier stage, thus improving patient outcomes.…”
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Artificial Intelligence in Uropathology by Katia Ramos Moreira Leite, Petronio Augusto de Souza Melo

“…AI, especially deep learning algorithms, has shown significant potential in improving the accuracy and efficiency of pathology workflows. …”
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What Strategy Central Nervous System Uses to Perform a Movement Balanced? Biomechatronical Simulation of Human Lifting by Ali Leylavi Shoushtari

“…The results show that the simulated postures are normal and the predicted motion is performed completely balanced.…”
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A Statistical Framework for Modeling Behavioral Engagement via Topic and Psycholinguistic Features: Evidence from High-Dimensional Text Data by Dan Li, Yi Zhang

“…This approach offers practical implications for optimizing algorithmic content ranking and fostering equitable visibility for marginalized digital labor groups.…”
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Understanding HLA-DQ in renal transplantation: a mini-review by Rajdeep Das, Neil S. Greenspan

“…Traditional serological or low-resolution typing often misclassifies mismatches, leading to inaccuracies in assessing immunogenicity and predicting outcomes. Emerging molecular mismatch algorithms refine immunogenicity assessments by analyzing amino acid differences and structural interactions. …”
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A Review of Generative Design Using Machine Learning for Additive Manufacturing by Parankush Koul

“…Generative design uses complex algorithms to automate the process of designing best-fit designs, mass customization, and customization to suit specific customer requirements with high efficiency and quality. …”
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Autoregressive integrated moving average model–based secure data aggregation for wireless sensor networks by Hongtao Song, Shanshan Sui, Qilong Han, Hui Zhang, Zaiqiang Yang

“…This fact calls for special requirements for network protocol design, security assessment models, and energy-efficient algorithms. Data aggregation is an effective energy conservation technique, which removes redundant information from the data aggregated from neighbor sensor nodes. …”
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Data-Driven Approaches for Estimation of EV Battery SoC and SoH: A Review by Shahid Gulzar Padder, Jayesh Ambulkar, Atul Banotra, Sudhakar Modem, Sidharth Maheshwari, Kolleboyina Jayaramulu, Chinmoy Kundu

“…In this study, machine learning algorithms exhibited substantial enhancements in predicting and maintaining the lifespan of electric vehicle batteries. …”
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Large‐scale identification of genetic design strategies using local search by Desmond S Lun, Graham Rockwell, Nicholas J Guido, Michael Baym, Jonathan A Kelner, Bonnie Berger, James E Galagan, George M Church

“…Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing.…”
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The Impact of Snow Cover on River Discharge Simulation: Insights from the Barandozchay River Basin by Haleh Hashemi, Hossein Rezaie, Keivan Khalili, Amin Amini

“…This study presents a comprehensive analysis aimed at predicting the discharge of the Barandozchay River using machine learning algorithms and meteorological data from both satellite and ground sources over the period from 2002 to 2022. …”
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence–Enabled ECGs by Scott Anjewierden, Donnchadh O'Sullivan, Kathryn E. Mangold, Grace Greason, Itzhak Zachi Attia, Francisco Lopez‐Jimenez, Paul A. Friedman, Samuel J. Asirvatham, Jason Anderson, Benjamin W. Eidem, Jonathan N. Johnson, Shisheer Havangi Prakash, Talha Niaz, Malini Madhavan

“…We aimed to develop novel artificial intelligence–enabled ECG algorithms for LVSD and RVSD detection in pediatric patients. …”
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Advancements in Herpes Zoster Diagnosis, Treatment, and Management: Systematic Review of Artificial Intelligence Applications by Dasheng Wu, Na Liu, Rui Ma, Peilong Wu

“…Classification tasks (85.2%) dominated AI applications, with neural networks, particularly multilayer perceptron and convolutional neural networks being the most frequently used algorithms. AI applications were analyzed across three domains: (1) diagnosis, where mobile deep neural networks, convolutional neural network ensemble models, and mixed-scale attention-based models have improved diagnostic accuracy and efficiency; (2) treatment, where machine learning models, such as deep autoencoders combined with functional magnetic resonance imaging, electroencephalography, and clinical data, have enhanced treatment outcome predictions; and (3) management, where AI has facilitated case identification, epidemiological research, health care burden assessment, and risk factor exploration for postherpetic neuralgia and other complications. …”
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AI-powered blockchain technology in industry 4.0, a review by Mohsen Soori, Roza Dastres, Behrooz Arezoo

“…Artificial Intelligence (AI) algorithms can be employed to enhance the security of the blockchain networks in the era of industry 4.0. …”
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Advancements in AI-Powered Electric Vehicle Routing: Multi-Constraint Optimization and Infrastructure Integration Approaches for Evolving EVs—A Survey by P. Anandha Prakash, R. Radha

“…Electric vehicles (EVs) have become essential tools in the worldwide shift to sustainable transportation, driven by advances in battery technology, charging infrastructure, and routing algorithms. This paper presents a comprehensive investigation of the emerging EV ecosystem through three key domains: electric automobiles, routing algorithms, and charging infrastructure. …”
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Multimodal dataset for sensor fusion in fall detection by Carla Taramasco, Miguel Pineiro, Pablo Ormeño-Arriagada, Diego Robles, David Araya

“…The success of developing effective detection algorithms is dependent on the availability of comprehensive datasets that integrate data from multiple synchronized sensors. …”
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Monitoring Pine Wilt Disease Using High-Resolution Satellite Remote Sensing at the Single-Tree Scale with Integrated Self-Attention by Wenhao Lv, Junhao Zhao, Jixia Huang

“…This study introduces several advanced self-attention algorithms into the task of satellite-based monitoring of pine wilt disease to enhance detection performance. …”
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Single target tracking in high-resolution satellite videos: a comprehensive review by Xin Huang, Ding Wang, Qiqi Zhu, Ying Zheng, Qingfeng Guan

“…To identify emerging research trends and opportunities, we classify established and emerging algorithms into three main categories and evaluate their performance on typical satellite videos. …”
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AI-aided short-term decision making of rockburst damage scale in underground engineering by Chukwuemeka Daniel, Shouye Cheng, Xin Yin, Zakaria Mohamed Barrie, Yucong Pan, Quansheng Liu, Feng Gao, Minsheng Li, Xing Huang

“…This study investigates the effectiveness of ensemble machine learning models optimized through Bayesian optimization (BO) in predicting rockburst damage scales. Nine classifier algorithms, including random forest (RF), were evaluated using a dataset of 254 samples. …”
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Performance evaluation of geopolymer masonry units: A hybrid approach combining laboratory testing and AI modeling by Md. Zia Ul Haq, Sandeep Singh, Tarak Vora, A.K. Dasarathy, Kaushik Bharti, Vanitha S, Priyadarshi Das, Laura Ricciotti

“…The study also employs nine machine learning algorithms on a dataset comprising 612 prism and 63 wallette data points, assessing performance based on six predictive metrics. …”
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High concentration formulation developability approaches and considerations by Jonathan Zarzar, Tarik Khan, Maniraj Bhagawati, Benjamin Weiche, Jasmin Sydow-Andersen, Alavattam Sreedhara

“…In order to accelerate and derisk development, new experimental and in-silico methods have emerged that can predict high concentration liabilities. Here, we review the challenges in developing high concentration formulations, the advances that have been made in establishing low mass and high-throughput predictive analytics, and advances in in-silico tools and algorithms aimed at identifying risks and understanding high concentration protein behavior.…”
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