Raman Spectra Classification of Pharmaceutical Compounds: A Benchmark of Machine Learning Models with SHAP-Based Explainability by Dimitris Kalatzis, Alkmini Nega, Yiannis Kiouvrekis

“…A diverse array of algorithms—including Support Vector Machines (SVMs), Random Forests, k-Nearest Neighbors (k-NN), Gradient Boosting (XGBoost, LightGBM), and 1D Convolutional Neural Networks (CNNs)—were evaluated on a publicly available dataset. …”
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Opportunistic Diagnostics of Dental Implants in Routine Clinical Photon-Counting CT Acquisitions by Maurice Ruetters, Holger Gehrig, Christian Mertens, Sinan Sen, Ti-Sun Kim, Heinz-Peter Schlemmer, Christian H. Ziener, Stefan Schoenberg, Matthias Froelich, Marc Kachelrieß, Stefan Sawall

“…Conventional CT scans, such as those of the cervical spine, have so far lacked the resolution to reliably evaluate dental structures or implants. This study evaluates the diagnostic utility of PCCT for visualizing peri-implant structures in routine clinical photon-counting CT acquisitions and assesses the influence of metal artifact reduction (MAR) algorithms on image quality. …”
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Quantum computing challenges and solutions in software industry—A multivocal literature review by Masaud Salam, Muhammad Ilyas

“…Subsequently, these challenges were examined deeply and determined that five of them are the most critical, these are ‘Lack of quantum specific algorithms, dev and testing methodologies’, ‘Difficult compilation and debugging’, ‘Lack of development tools and technology’, ‘Lack of development guidelines & Quality Assurance Standards’ and ‘Lack of professional expert’, together founding over 30% of occurrences. …”
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Automatic text generation system for endangered languages based on conditional generative adversarial networks by Zhong Luo

“…Future research directions include optimizing CGAN parameters using algorithms like particle swarm optimization, refining discriminator outputs in loss calculations, and incorporating cultural and linguistic features specific to endangered languages to improve the quality of the generated texts.…”
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Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis by Hanglin Cheng, Yihao Li, Ruiheng Zhang, Weiguang Zhang

“…Traditional Foreign Object Debris (FOD) detection methods face challenges such as difficulties in large-size data acquisition and the ineffective application of detection algorithms with high accuracy. …”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…For instance, machine learning models can evaluate patient records, lifestyle factors, and genetic information to deliver precise risk assessments and personalized recommendations. …”
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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…At the same time, data scarcity affects the accuracy and comprehensiveness of model evaluation and recommendation. This is a pain point in multimodal recommendation. …”
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Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

“…In addition, eight different machine learning algorithms were applied for prediction, and the prediction performances of these algorithms were comprehensively evaluated using the receiver operating characteristic curve, area under the curve (AUC), calibration curve analysis, and decision curve analysis and confusion matrix.ConclusionsUsing LASSO regression analysis, leukocyte, neutrophil, red blood cell, hemoglobin, platelet, and monocyte-to-lymphocyte ratios were identified as risk factors for HF. …”
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Opposition-based chaotic evolution for optimization by Tianshui Li, Yan Pei

“…The findings support the broader applicability of OBCE in real-world engineering design problems where solution quality and efficiency are critical.…”
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DIFshilling: A Diffusion Model for Shilling Attacks by Weizhi Chen, Xingkong Ma, Bo Liu

“…Many current approaches either fail to capture the natural distribution of real user data or are highly tailored to specific RS algorithms, limiting their general applicability and effectiveness. …”
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Triple-layered security system: reliable and secured image communications over 5G and beyond networks by Tarek Srour, Mohsen A. M. El-Bendary, Mostafa Eltokhy, Atef E. Abouelazm

“…The advanced wireless networks require reliable graded complexity security tools with various levels capabilities, therefore, the proposed adapted complexity/levels security system is suitable and applicable for 5G/beyond networks.…”
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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Data extraction focused on device types, sensor quality, compliance with health standards, and the predictive algorithms employed.ResultsWearable devices show promise in correlating physiological markers with CP, but few studies integrate predictive models. …”
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Comparative Study on EDM Wire Cutting and CO2 Laser Cutting for High‐Precision Stainless Steel Sheet Processing by A. Parthiban, K. Ananthakumar, S. Ajith Arul Daniel, S. Sivaganesan, T. Sathish, Jayant Giri, A. Johnson Santhosh, Ahmad O. Hourani

“…This study conducts a comprehensive experimental analysis of these techniques, focusing on their performance when cutting stainless steel grades AISI 316L and 304. The research evaluates key process parameters influencing the cut quality, aiming to achieve minimal surface roughness. …”
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Capability-driven framework to automate discovery of bounded contexts in large-scale requirements engineering by Shohreh Ajoudanian, Maryam Nooraei Abadeh

“…We also provide the applicability of the approach from various points of view including quality and stability of bounded contexts, average precision, and query assessment. …”
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Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism. by Yutong Liu, Shile Zhang

“…Improving translation quality and efficiency is one of the key challenges in the field of Natural Language Processing (NLP). …”
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A Low-Cost Antipodal Vivaldi Antenna-Based Peanut Defect Rate Detection System by Yuanyuan Yin, Fangyan Ma, Xiaohong Liu, Shuhao Wang, Junjie Xia, Liqing Zhao

“…As a result, it offers an affordable and practical solution for quality control in peanut production, showing great potential for wide application in the peanut industry.…”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…By adopting scalable AI models and fostering interdisciplinary collaborations, healthcare systems can overcome existing barriers, integrating AI seamlessly into infection control policies and ultimately enhancing patient safety and care quality. Further research is needed to evaluate cost-effectiveness, real-world applications, and strategies (e.g., clinician training and the integration of explainable AI) to improve trust and broaden clinical adoption.…”
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Harnessing quantum power: Revolutionizing materials design through advanced quantum computation by Zikang Guo, Rui Li, Xianfeng He, Jiang Guo, Shenghong Ju

“…We introduce the loop framework for QUBO‐empowered materials design, including constructing high‐quality datasets that capture critical material properties, employing tailored computational methods for precise material modeling, developing advanced figures of merit to evaluate performance metrics, and utilizing quantum optimization algorithms to discover optimal materials. …”
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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…Secondly, to address missing values and noise in the data, preprocessing methods such as denoising, normalization, and feature extraction are employed to ensure data quality and model accuracy. Finally, in the selection of ML models, this study experiments with several common algorithms, including extreme gradient boosting (XGBoost), support vector machine (SVM), random forest (RF), and deep neural network (DNN). …”
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Multi-Class Classification Methods for EEG Signals of Lower-Limb Rehabilitation Movements by Shuangling Ma, Zijie Situ, Xiaobo Peng, Zhangyang Li, Ying Huang

“…However, the existing multi-class classification methods for motor imagery EEG (MI-EEG) signals are hindered by low signal quality and limited accuracy, restricting their practical application. …”
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