Design and Optimization of Optical NAND and NOR Gates Using Photonic Crystals and the ML-FOLD Algorithm by Alireza Mohammadi, Fariborz Parandin, Pouya Karami, Saeed Olyaee

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Sustainable Innovations in the Food Industry through Artificial Intelligence and Big Data Analytics by Saurabh Sharma, Vijay Kumar Gahlawat, Kumar Rahul, Rahul S Mor, Mohit Malik

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Investigation of ML algorithms for prediction of CFD data of fluid flow inside a packed-bed reactor by Yujiang Qiu, Pinxiao Liu

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Automation of image processing through ML algorithms of GRASS GIS using embedded Scikit-Learn library of Python by Polina Lemenkova

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Prediction of performance and emission features of diesel engine using alumina nanoparticles with neem oil biodiesel based on advanced ML algorithms by M. S. Aswathanrayan, N. Santhosh, Srikanth Holalu Venkataramana, Kurugundla Sunil Kumar, Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Sameer Algburi, Osamah J. Al-sareji, A. Bhowmik

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AI-driven innovation in antibody-drug conjugate design by Heather A. Noriega, Xiang Simon Wang

Subjects: “…AI/ML (artificial intelligence/machine learning)…”
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CMIP6 multi-model ensemble projection of reference evapotranspiration using machine learning algorithms by Milad Nouri, Shadman Veysi

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A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration by Victor Barbosa Slivinskis, Isabela Agi Maluli, Joshua Seth Broder

“…Our objective was to evaluate the sensitivity, specificity, and accuracy of a machine learning (ML) algorithm using publicly available data to predict medical device recalls by the FDA. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

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FTIR-Based Microplastic Classification: A Comprehensive Study on Normalization and ML Techniques by Octavio Villegas-Camacho, Iván Francisco-Valencia, Roberto Alejo-Eleuterio, Everardo Efrén Granda-Gutiérrez, Sonia Martínez-Gallegos, Daniel Villanueva-Vásquez

“…The study assessed the performance of ML algorithms, such as k-nearest neighbors (k-NN), support vector machines (SVM), naive Bayes (NB), random forest (RF), and artificial neural networks architectures (including convolutional neural networks (CNNs) and multilayer perceptrons (MLPs)). …”
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ML-Based Quantitative Analysis of Linguistic and Speech Features Relevant in Predicting Alzheimer’s Disease by Tripti Tripathi, Rakesh Kumar

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Emerging Trends in AI-Based Soil Contamination Monitoring and Prevention by Cosmina-Mihaela Rosca, Adrian Stancu

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Developing an IoT and ML-driven platform for fruit ripeness evaluation and spoilage detection: A case study on bananas by Rajini M, Persis Voola

“…Food waste is a significant global problem that demands immediate action to reduce it. …”
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Applications of Machine Learning in Food Safety and HACCP Monitoring of Animal-Source Foods by Panagiota-Kyriaki Revelou, Efstathia Tsakali, Anthimia Batrinou, Irini F. Strati

“…Studies that link ML with HACCP monitoring in ASFs are limited. The present review provides an overview of ML, feature extraction, and selection algorithms employed for food safety. …”
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Advancing breast cancer prediction: Comparative analysis of ML models and deep learning-based multi-model ensembles on original and synthetic datasets. by Kazi Arman Ahmed, Israt Humaira, Ashiqur Rahman Khan, Md Shamim Hasan, Mukitul Islam, Anik Roy, Mehrab Karim, Mezbah Uddin, Ashique Mohammad, Md Doulotuzzaman Xames

“…This study employs various machine learning (ML) algorithms, including KNN, SVM, ANN, RF, XGBoost, ensemble models, AutoML, and deep learning (DL) techniques, to enhance breast cancer diagnosis. …”
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Comparing AI/ML approaches and classical regression for predictive modeling using large population health databases: Applications to COVID-19 case prediction by Lise M. Bjerre, Cayden Peixoto, Rawan Alkurd, Robert Talarico, Rami Abielmona

“…Objectives: This retrospective cohort study aimed to compare the predictive performance of AI/ML algorithms against conventional multivariate logistic regression models using linked health administrative data. …”
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Predictive Model for Erosion Rate of Concrete Under Wind Gravel Flow Based on K-Fold Cross-Validation Combined with Support Vector Machine by Yanhua Zhao, Kai Zhang, Aojun Guo, Fukang Hao, Jie Ma

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Artificial intelligence in the food industry: innovations and applications by Hang Yang, Wenxuan Jiao, Lingyun Zouyi, Hongli Diao, Shibin Xia

“…AI technologies, including machine learning (ML) algorithms and computer vision systems, are widely used to optimize supply chains, predict demand, reduce waste, and enhance food safety and quality monitoring. …”
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Improving machine learning models through explainable AI for predicting the level of dietary diversity among Ethiopian preschool children by Gizachew Mulu Setegn, Belayneh Endalamaw Dejene

“…We evaluated it using accuracy, precision, recall, F1_score, and receiver operating characteristic (ROC)-based evaluation techniques. Results The ensemble ML models exhibited robust predictive performance, and light gradient boosting outperformed the other ensemble ML algorithms by 95.3%. …”
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A Novel Dataset for Early Cardiovascular Risk Detection in School Children Using Machine Learning by Rafael Alejandro Olivera Solís, Emilio Francisco González Rodríguez, Roberto Castañeda Sheissa, Juan Valentín Lorenzo-Ginori, José García

“…We conducted a rigorous performance evaluation of 10 machine learning (ML) algorithms to classify cardiovascular risk into two categories: at risk and not at risk. …”
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