Intelligent Photolithography Corrections Using Dimensionality Reductions by Parag Parashar, Chandni Akbar, Tejender S. Rawat, Sparsh Pratik, Rajat Butola, Shih H. Chen, Yung-Sung Chang, Sirapop Nuannimnoi, Albert S. Lin

“…In this work, we use dimensionality reduction (DR) algorithms to reduce the computation time of complex OPC/EPC problems while the prediction accuracy is maintained. …”
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Unraveling genetic predisposition and oxidative stress in vitiligo development and the role of artificial intelligence (AI) in diagnosis and management by Kocić Hristina, Lotti Torello, Jevtović-Stoimenov Tatjana, Wollina Uwe, Valle Yan, Lukić Stevo, Klisić Aleksandra

“…By analysing vast datasets, AI algorithms can identify patterns within complex genetic markers and clinical features, facilitating earlier and more precise detection of vitiligo. …”
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Impact of bridging the gap between Artificial Intelligence and nanomedicine in healthcare by Divyam Mishra, Bhavishya Chaturvedi, Vishal Soni, Dhairya Valecha, Megha Goel, Jamilur R. Ansari

“…We will also assess the long-term implications of lipid nanoparticles in drug delivery applications. Machine Learning algorithms are employed to create data-driven adaptive nanomaterials and paradigms, further advancing the field. …”
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Objective determination of initiation stress and damage stress in rock failure using acoustic emission and digital image correlation by Peng Liang, Yanbo Zhang, Xulong Yao, Guangyuan Yu, Qiang Han, Junling Liu

“…Additionally, an accurate identification and determination method for rock initiation and damage stresses based on acoustic emission monitoring was proposed, utilizing the Kneedle algorithm to automatically detect inflection points and identify sudden increases in the curve. …”
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Decoding Schizophrenia: How AI-Enhanced fMRI Unlocks New Pathways for Precision Psychiatry by Valeria Di Stefano, Martina D’Angelo, Francesco Monaco, Annarita Vignapiano, Vassilis Martiadis, Eugenia Barone, Michele Fornaro, Luca Steardo, Marco Solmi, Mirko Manchia, Luca Steardo

“…Moreover, ethical considerations surrounding data integrity, algorithmic transparency, and patient individuality must guide AI’s integration into psychiatry. …”
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Ethical framework for responsible foundational models in medical imaging by Debesh Jha, Gorkem Durak, Abhijit Das, Jasmer Sanjotra, Onkar Susladkar, Suramyaa Sarkar, Ashish Rauniyar, Nikhil Kumar Tomar, Linkai Peng, Sirui Li, Koushik Biswas, Ertugrul Aktas, Elif Keles, Matthew Antalek, Zheyuan Zhang, Bin Wang, Xin Zhu, Xin Zhu, Hongyi Pan, Deniz Seyithanoglu, Alpay Medetalibeyoglu, Vanshali Sharma, Vedat Cicek, Amir A. Rahsepar, Rutger Hendrix, Rutger Hendrix, A. Enis Cetin, Bulent Aydogan, Mohamed Abazeed, Frank H. Miller, Rajesh N. Keswani, Rajesh N. Keswani, Hatice Savas, Sachin Jambawalikar, Daniela P. Ladner, Amir A. Borhani, Concetto Spampinato, Concetto Spampinato, Michael B. Wallace, Michael B. Wallace, Ulas Bagci

“…This framework emphasizes robust privacy safeguards, systematic bias detection and mitigation strategies, and mechanisms for maintaining meaningful human oversight. …”
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Determinants and risk prediction models for frailty among community-living older adults in eastern China by Lin Qi, Lin Qi, Jianyu Liu, Xuhui Song, Xinle Wang, Mengmeng Yang, Xinyi Cao, Yan He

“…Predictive models were constructed using decision trees, random forests, and XGBoost algorithms, implemented in R software (version 4.4.2). …”
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Comprehensive Blood Metabolome and Exposome Analysis, Annotation, and Interpretation in E-Waste Workers by Zhiqiang Pang, Charles Viau, Julius N. Fobil, Niladri Basu, Jianguo Xia

“…A specialized computational workflow was established for exposomics data analysis, incorporating two curated reference libraries for metabolome and exposome profiling. Two feature detection algorithms, <i>asari</i> and <i>centWave</i>, were applied. …”
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Analysis of follow-up data in large biobank cohorts: a review of methodology by Anastassia Kolde, Anastassia Kolde, Merli Koitmäe, Merli Koitmäe, Meelis Käärik, Märt Möls, Krista Fischer, Krista Fischer

“…We address four primary issues: left-truncation of the data, computational inefficiency of standard model-fitting algorithms, relatedness among individuals, and model misspecification. …”
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Diagnostic Utility of ¹⁸F-FDG PET/CT in Infective Endocarditis by Corina-Ioana Anton, Alice-Elena Munteanu, Mihaela Raluca Mititelu, Militaru Alexandru Ștefan, Cosmin-Alexandru Buzilă, Adrian Streinu-Cercel

“…Its integration into diagnostic algorithms may improve clinical management and outcomes in complex IE cases.…”
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Integrating machine learning and single-cell sequencing to identify shared biomarkers in type 1 diabetes mellitus and clear cell renal cell carcinoma by Yi Li, Rui Zeng, Rui Zeng, Yuhua Huang, Yumin Zhuo, Jun Huang

“…Subsequently, the LASSO and SVM algorithms were employed to identify shared hub genes between the two diseases. …”
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Sustainable Energy and Exergy Analysis in Offshore Wind Farms Using Machine Learning: A Systematic Review by Hamid Reza Soltani Motlagh, Seyed Behbood Issa-Zadeh, Abdul Hameed Kalifullah, Arife Tugsan Isiacik Colak, Md Redzuan Zoolfakar

“…By integrating theoretical insights with empirical evidence, this study proposes a unified framework that leverages ML algorithms to optimize turbine performance, reduce maintenance costs, and minimize environmental impacts. …”
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Advanced Learning Technologies for Intelligent Transportation Systems: Prospects and Challenges by Ruhul Amin Khalil, Ziad Safelnasr, Naod Yemane, Mebruk Kedir, Atawulrahman Shafiqurrahman, NASIR SAEED

“…In addition to shedding light on the state-of-the-art DL algorithms, we also explore potential applications of DL and large language models (LLMs) in ITS, including traffic flow prediction, vehicle detection and classification, road condition monitoring, traffic sign recognition, and autonomous vehicles. …”
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Ensemble deep learning and EfficientNet for accurate diagnosis of diabetic retinopathy by Lakshay Arora, Sunil K. Singh, Sudhakar Kumar, Hardik Gupta, Wadee Alhalabi, Varsha Arya, Shavi Bansal, Kwok Tai Chui, Brij B. Gupta

“…This framework takes help from the EfficientNet Machine Learning algorithms and employing advanced CNN layering techniques. …”
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Adult Hope Scale: validation in older adults by Kate Labrosciano, Jillian Dorrian, Braam Lowies, Roslyn Russell, Kurt Lushington

“…Dimensionality was tested by (i) bifactor modelling (one-factor, two-factor and a bifactor model with a general factor, Hope, and two specific factors, Agency and Pathways) and (ii) exploratory graph analysis (which uses community detection algorithms to cluster variables into factors). …”
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Enhancing Cross-Modal Camera Image and LiDAR Data Registration Using Feature-Based Matching by Jennifer Leahy, Shabnam Jabari, Derek Lichti, Abbas Salehitangrizi

“…Registering light detection and ranging (LiDAR) data with optical camera images enhances spatial awareness in autonomous driving, robotics, and geographic information systems. …”
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Analysis of Minerals Using Handheld Laser-Induced Breakdown Spectroscopy Technology by Naila Mezoued, Cécile Fabre, Jean Cauzid, YongHwi Kim, Marjolène Jatteau

“…Mineral spectra can serve as reference data to (i) identify relevant emission lines and spectral ranges for specific minerals, (ii) be compared to unknown LIBS spectra for mineral identification, or (iii) constitute input data for machine learning algorithms.…”
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Molecular profile of salivary gland tumors: discovering new targets for therapy by A. V. Ignatova, Yu.  V. Alymov, I.  S. Romanov

“…The search for specific therapeutically significant markers and mutations for various histological types of salivary gland tumors may allow the development of a diagnostic algorithm and improve patient treatment results.Aim. …”
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A compression method of educational material for special disciplines of technical University by Konstantin P. Baslyk

“…The vertices weight is detected as a time spent on the explanation of element contents. …”
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Biomechanical simulations of intracerebral hemorrhage expansion show tissue displacement has significant impact on electrical impedance tomography results by Antti Paldanius, Jussi Toivanen, Nina Forss, Daniel Strbian, Ville Kolehmainen, Jari Hyttinen

“…However, the effects of displaced CSF could be easier to detect with EIT than the ICH blood volume increase and thus could be used as an indicator of HE in EIT bedside monitoring of ICH and improve the detectability of HE, especially for ICH located deep in the brain. …”
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