QFCOI-Enhancing Objective Quality Assessment for Compressed Omnidirectional Images With Fusion of Measures by Marek Simka, Ladislav Polak, Adam Zizien, Karel Fliegel

“…The feature metrics selection was based on statistical performance and ability to capture key aspects of image quality, including structural preservation, visual information fidelity, and artifact sensitivity. To optimize predictive performance of QFCOI, a genetic algorithm was utilized to determine optimal weight coefficients, maximizing the monotonic correlation with subjective quality scores. …”
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Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…The findings contribute to a more accurate and reliable identification of faults, offering significant advancements in the field of machinery health monitoring and predictive maintenance.…”
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Validation study of bullous pemphigoid and pemphigus vulgaris recording in routinely collected electronic primary healthcare records in England by Yana Vinogradova, Julia Hippisley-Cox, Sonia Gran, Sinéad M Langan, Monica S M Persson, Karen E Harman, Kim S Thomas

“…We assessed the positive predictive value (PPV) for bullous pemphigoid and pemphigus vulgaris primary care Read codes in the Clinical Practice Research Datalink (CPRD) using linked inpatient data (Hospital Episode Statistics (HES)) as the diagnostic benchmark.Setting Adult participants with bullous pemphigoid or pemphigus vulgaris registered with HES-linked general practices in England between January 1998 and December 2017. …”
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A Comprehensive Review of the Main Heavyweight and Lightweight SDLC for Big Data Analytics Systems (BDAS) by David Alejandro Montoya-Murillo, Sergio Galvan-Cruz, Manuel Mora, Estela Lizbeth Munoz Andrade

“…Big Data Analytics Systems (BDAS) are software systems developed with descriptive, predictive, or prescriptive decision-making purposes, and currently are implemented in diverse domains – i.e. …”
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Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions by Shumaila Javaid, Ruhul Amin Khalil, Nasir Saeed, Bin He, Mohamed-Slim Alouini

“…We outline the current architecture of ISATNs and highlight the significant role LLMs can play in optimizing data flow, signal processing, and network management to advance 5G/6G communication technologies through advanced predictive algorithms and real-time decision-making. …”
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Validation of Self-reported Medical Condition in the Taiwan Biobank by Chi-Shin Wu, Le-Yin Hsu, Chen-Yang Shen, Wei J. Chen, Shi-Heng Wang

“…Integrating complementary databases, such as clinical diagnoses, prescription records, and medical procedures, can enhance accuracy through customized algorithms based on disease categories and participant characteristics and optimize sensitivity or positive predictive values to align with specific research objectives.…”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…Empirically, we draw on a cross-sectional research project, assessing the predictive power of linguistic data processing algorithms and the experiences of financial analysts in cost structuring contexts. …”
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Modeling Universal Thermal Climate Index Thermal Stress in Iran’s Hot Zones Using Neural Networks and Naïve Bayes by Sajad Zare, Reza Esmaeili, Rasoul Hemmatjo

“…Conclusion: In the models for hot-dry regions, both algorithms predicted Ta and then Tmrt as the principal factors. …”
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Artificial Intelligence in Cardiovascular Diagnosis: Innovations and Impact on Disease Screenings by Amber Ahmad, Sahil Ahmad, Rida Ahmad, Jahnavi Bodi, Abdulla Mohamed, Ahmad Wasim

“…Introduction: Artificial intelligence (AI) is making waves in health care, with ECGs and other imaging data leveraged to diagnose or predict cardiovascular diseases (CVDs). Materials and methods: Various AI models as well as algorithms, such as machine learning (ML) and deep learning (DL) algorithms, have shown good results in the detection of diseases like heart failure, atrial fibrillation, coronary artery disease, and valvular heart disease. …”
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Chaotic Mountain Gazelle Optimizer Improved by Multiple Oppositional-Based Learning Variants for Theoretical Thermal Design Optimization of Heat Exchangers Using Nanofluids by Oguz Emrah Turgut, Mustafa Asker, Hayrullah Bilgeran Yesiloz, Hadi Genceli, Mohammad AL-Rawi

“…The Mountain Gazelle Optimizer is a recently developed metaheuristic algorithm that simulates the foraging behaviors of Mountain Gazelles. …”
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Wave propagation-based tests for concrete piles – an overview by Reham Samaan, Abdelsalaam Mokhtar, Mohamed Saafan, Ahmed Ebid

“…This investigation establishes the practical and theoretical basis for implementing advanced machine learning predictive models that combine previous records with pattern recognition algorithms, potentially converting traditional PIT interpretation from an uncertain process to a reliable and precise evaluation system. …”
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A simultaneous post-LASIK sequential bilateral implantation of multifocal IOLs aimed at refraction correction. A clinical case by E. N. Eskina, A. V. Belogurova, A. I. Fisenko

“…The compliance with the modified algorithms of pre-and intraoperative behavior of the operating team, thorough preparation of the patient, careful calculation of the IOL allowed us to obtain the predictive refractive result with a high level of visual satisfaction and absence of undesirable postoperative phenomena. …”
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Detecting anomalies in graph networks on digital markets. by Agata Skorupka

“…Methods are compared against each other, and state-of-the-art results from the literature and a new algorithm is proposed. The goal is to find an efficient method suitable for threat detection, both in terms of predictive performance and computational efficiency. …”
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Blood-based biomarkers in patients with non-small cell lung cancer treated with immune checkpoint blockade by Yo-Ting Tsai, Jeffrey Schlom, Renee N. Donahue

“…Integration of multiple blood-based biomarkers into comprehensive panels or algorithms also has the potential to enhance predictive accuracy. …”
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Numerical modeling and neural network optimization for advanced solar panel efficiency by Udit Mamodiya, Indra Kishor, Mohammed Amin Almaiah, Monia Hamdi, Rami Shehab, Tayseer Alkhdour

“…Besides, an advanced hybrid model based on CNN-LSTM is applied to solar energy forecasting for predictive control of the maximum energy yield. Experimental validation was performed using UTL 335W and 330W PV modules, where real-time data acquisition was followed by AI-driven optimization. …”
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A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection by K. Anup Kumar, C. Vanmathi

“…Furthermore, the system has a false positive rate (FPR) of 10.7% and a positive predictive value (PPV) of 90.8%, demonstrating its capacity to reduce wrong diagnosis while prioritizing true positive instances. …”
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Neurotechnological Approaches to Cognitive Rehabilitation in Mild Cognitive Impairment: A Systematic Review of Neuromodulation, EEG, Virtual Reality, and Emerging AI Applications by Evgenia Gkintoni, Stephanos P. Vassilopoulos, Georgios Nikolaou, Apostolos Vantarakis

“…Emerging AI applications showed potential for personalized assessment and intervention through predictive modeling and adaptive algorithms. <i>Conclusions:</i> Neurotechnological approaches offer promising avenues for MCI rehabilitation, with the most substantial evidence for integrated interventions targeting multiple mechanisms. …”
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Novel neoadjuvant therapies for muscle‐invasive bladder cancer: Systematic review and meta‐analysis by Shugo Yajima, Naoki Imasato, Hitoshi Masuda

“…Randomized trials are needed to establish optimal treatment algorithms and validate predictive biomarkers.…”
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Molecular biomarkers in salivary diagnostic materials: Point-of-Care solutions — PoC-Diagnostics and -Testing by Ziyad S. Haidar

“…Henceforth, ongoing advancements are expected to further integrate predictive analytics into our routine clinical practice, ultimately improving patient outcomes through personalized, cost-effective, and timely care, thereby enhancing overall healthcare quality and efficiency. …”
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Artificial Intelligence in Advancing Algal Bioactive Ingredients: Production, Characterization, and Application by Bingbing Guo, Xingyu Lu, Xiaoyu Jiang, Xiao-Li Shen, Zihao Wei, Yifeng Zhang

“…This review examines the multidimensional mechanisms by which AI enables and optimizes these processes: (1) AI-powered predictive models, integrated with machine learning algorithms (MLAs), Industry 4.0, and other advanced digital systems, support real-time monitoring and control of intelligent bioreactors, allowing for accurate forecasting of cultivation yields and market demand. (2) AI facilitates in-depth analysis of gene regulatory networks and key metabolic pathways, enabling precise control over the biosynthesis of targeted compounds. (3) AI-based spectral imaging and image recognition techniques enable rapid and reliable identification, classification, and quality assessment of active components. (4) AI accelerates the transition from mass production to the development of personalized medical and functional nutritional products. …”
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