Challenges and opportunities with ChatGPT in oral oncology: The journey ahead by Ribwar Arsalan Mohammed, Sirwan Khalid Ahmed

“…ChatGPT's use of natural language processing enables it to analyze complex medical data, aiding in early cancer detection and personalized treatment planning based on evidence-based guidelines. Furthermore, as an educational tool, ChatGPT promotes better understanding of medical concepts among healthcare professionals and patients alike, fostering informed decision-making and active participation in healthcare. …”
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Interpretable machine learning for predicting optimal surgical timing in polytrauma patients with TBI and fractures to reduce postoperative infection risk by Xing Han, Jia-Hui Zhang, Xin Zhao, Xi-Guang Sang

“…SHAP and LIME algorithms were utilized for model interpretation, elucidating the importance and predictive thresholds of the variables. …”
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A comprehensive review of flood damage in mountainous regions: challenges, solutions, and advanced management technologies by Mohammad Roohi, Jila Dehghani, Maryam Irani, Paramiss Mina

“…The results of the study show that flood planning and control can be greatly enhanced by fusing advanced technologies such as LiDAR, remote sensing, and machine learning with local expertise. …”
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Transformer network for time series prediction via wavelet packet decomposition by Zhichao Wu, Aiye Shi, Yan Ping Tao

“…The accurate prediction of time series data iscritical for making decisions and planning. In the real world, non-stationarytime series data with statistical properties shift over time, making predictionmore challenging. …”
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Orbital Analysis of a Dual Asteroid System Explorer Based on the Finite Element Method by Linli Su, Wenyu Feng, Lie Yang, Zichen Fan, Mingying Huo, Naiming Qi

“…The insights gained from the analysis of orbital characteristics can inform the design of landing trajectories for binary asteroid systems and provide data for deep learning algorithms that are aimed at optimizing such orbits. …”
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Production monitoring and machine tracking in underground mines based on a collision avoidance system: A case study by Artur Skoczylas, Natalia Duda-Mróz, Wioletta Koperska, Paweł Stefaniak, Paweł Śliwiński

“…Consequently, the development of validation algorithms, including error correction and adaptive filtering, was imperative. …”
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Predictors of evacuation behavior: dataset on respondents’ route choice and web interaction by Dajana Snopková, Martin Tancoš, Lukáš Herman, Vojtěch Juřík

“…This dataset offers diverse research opportunities, particularly in emergency evacuation planning, where understanding evacuation choices in simulations can inform real-world strategies. …”
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Comment on “Odontogenic Tumors: A Challenge for Clinical Diagnosis and an Opportunity for AI Innovation” by Hinpetch Daungsupawong, Viroj Wiwanitkit

“…Dear Editor“Odontogenic Tumors: A Challenge for Clinical Diagnosis and an Opportunity for AI Innovation. [1]” is informative and we would like to comment on this article.  …”
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Big data and AI for gender equality in health: bias is a big challenge by Anagha Joshi, Anagha Joshi, Anagha Joshi

“…Despite these promises, machine learning applications are not widely adapted in clinical care due to many issues including ethical concerns, patient privacy, informed consent, algorithmic biases, data quality and availability, and education and training of health care professionals. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…The proposed approach employs Decision Tree (DT) algorithms to uncover patterns linked to service failures. …”
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Integrating Multi-Variable Driving Factors to Improve Land Use & Land Cover Classification Accuracy using Machine Learning Approaches: A Case Study from Lombok Island by Miftahul Irsyadi Purnama, Hüseyin Oğuz Çoban

“…These results provide essential insights for land management strategies, enabling policymakers and stakeholders to make informed decisions on sustainable development, urban planning, and environmental conservation in rapidly changing landscapes. …”
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AirQuaNet: A Convolutional Neural Network Model With Multi-Scale Feature Learning and Attention Mechanisms for Air Quality-Based Health Impact Prediction by Sreeni Chadalavada, Suleyman Yaman, Abdulkadir Sengur, Ravinesh C. Deo, Abdul Hafeez-Baig, Tracy Kolbe-Alexander, Niranjana Sampathila, U. Rajendra Acharya

“…Predicting air quality and associated health impacts is crucial for early intervention and informed policy planning. This work presents Air Quality Network (AirQuaNet), a novel convolutional neural network (CNN) designed to predict air quality levels accurately. …”
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AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…The proposed system offers real-time alerts and forecasts, facilitating proactive water resource management, agricultural planning, and disaster preparedness. Moreover, the research conducts a comparative evaluation of various machine learning models to identify the most effective algorithms for different climatic zones and crop types. …”
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Highway Rest Area Truck Parking Occupancy Prediction Using Machine Learning: A Case Study from Poland by Artur Budzyński, Maria Cieśla

“…This study addresses this gap by applying supervised machine learning algorithms to predict hourly occupancy levels of truck parking lots at highway rest areas using a dataset collected from digital monitoring systems in Poland. …”
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Integrating Machine Learning, SHAP Interpretability, and Deep Learning Approaches in the Study of Environmental and Economic Factors: A Case Study of Residential Segregation in Las... by Jingyi Liu, Yuxuan Cai, Xiwei Shen

“…The methodology of this study is generalizable, offering a reproducible framework for future segregation studies in other cities and informing equitable urban planning and environmental policy.…”
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Automatic screening for posttraumatic stress disorder in early adolescents following the Ya’an earthquake using text mining techniques by Yuzhuo Yuan, Yuzhuo Yuan, Zhiyuan Liu, Wei Miao, Xuetao Tian

“…BackgroundSelf-narratives about traumatic experiences and symptoms are informative for early identification of potential patients; however, their use in clinical screening is limited. …”
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Time to Disease Control with Dupilumab for Bullous Pemphigoid: A Systematic Review and Meta-analysis by Laurence Mainville, Lily Xu, Vincent Piguet, Aaron M. Drucker, David O. Croitoru

“…It was not possible to assess predictors of response using pre-planned meta-regression. Randomized controlled trials are needed to determine dupilumab’s place in therapeutic algorithms for BP. …”
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Ethical Challenges of Using the Internet of Behavior in the Medical and Healthcare Practice by Zahra Sadeqi-Arani, Esmaeil Mazroui Nasrabadi

“…Additionally, reliance on algorithms for IoB data analysis should not diminish human oversight in healthcare decision-making. …”
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Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…In forestry, better management practices can minimize the environmental impact of logging. In urban planning, accurate gas emission maps can inform the design of green spaces and other urban features, helping reduce emissions and health impacts on city populations.Additionally, this research can generate dense datasets for atmospheric chemistry, climate, and air quality models. …”
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Predicting patient outcomes and risk for revision surgery after hip and knee replacement surgery: study protocol for a comparison of modelling approaches using the Swiss National J... by Léonie Hofstetter, Nathalie Schweyckart, Christof Seiler, Christian Brand, Laura C. Rosella, Mazda Farshad, Milo A. Puhan, Cesar A. Hincapié

“…Abstract Background Prediction of postoperative patient-reported outcomes and risk for revision surgery after total hip arthroplasty (THA) or total knee arthroplasty (TKA) can inform clinical decision-making, health resource allocation, and care planning. …”
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