Combination of machine learning and data envelopment analysis to measure the efficiency of the Tax Service Office by Shofinurdin Soffan, Arif Bramantoro, Ahmad A. Alzahrani

Subjects: “…Machine learning…”
Get full text

Data-driven analysis of hysteresis and stability in perovskite solar cells using machine learning by Sharun Parayil Shaji, Wolfgang Tress

Get full text

Data-driven analysis of climate impact on tomato and apple prices using machine learning by Sunghyun Yoon, Tae-Hwa Kim, Dong Sub Kim

Get full text

Data-driven evaluation of background radiation safety using machine learning and statistical analysis by Muhammad Abid, Muhammad Shahid

Get full text

The Role of Big Data Analytics in Revolutionizing Diabetes Management and Healthcare Decision-Making by Muhammad Nauman, Ahmad S. Almadhor, Mohammed Albekairi, Ali R. Ansari, Muhammad A. B. Fayyaz, Raheel Nawaz

Subjects: “…Big data analytics…”
Get full text

#GAMEADDICTED: A Machine Learning Framework for Digital Game Addiction Detection and Early Intervention by Esra Kahya Ozyirmidokuz, Bekir Asim Celik, Eduard Alexandru Stoica

Subjects: Get full text

A comprehensive diagnostic framework for hepatitis C using structured data and predictive analytics by Behnaz Motamedi, Balázs Villányi

“…This study posits that a structured preprocessing and feature selection methodology might substantially improve the classification accuracy and generalizability of machine learning (ML) models in predicting stages of hepatitis C virus (HCV) using clinical and demographic data. …”
Get full text

Investigating banks’ social media content and consumer reactions with machine learning by Gombos Nóra, Julianna, Vlaszov Artúr, Bíró-Szigeti Szilvia, Molontay Roland

Subjects: Get full text

Machine-learning-based analytics for risk forecasting of anaphylaxis during general anesthesia by Shuang Liu, Yasuyuki Suzuki, Toshihiro Yorozuya, Masaki Mogi

“…After data pre-processing, the performance of five classification methods: Logistic Regression Analysis, Support Vector Machine, Random Forest, Linear Discriminant Analysis, and Naïve Bayes), which were integrated with four feature selection methods (Recursive Feature Elimination, Chi-Squared Method, Correlation-based Feature Selection, and Information Gain Ratio), was evaluated using two-layer cross-validation. …”
Get full text

Analysis and prediction of atmospheric ozone concentrations using machine learning by Stephan Räss, Stephan Räss, Markus C. Leuenberger, Markus C. Leuenberger

Subjects: Get full text

Predictive Analytics in Maternal Health: A Machine Learning Approach for Classification of Preeclampsia by Pakiza Amin, Saima Gulzar Ahmad, Hikmat Ullah Khan, Ehsan Ullah Munir, Naeem Ramzan

Get full text

Physics-based and data-driven hybrid modeling in manufacturing: a review by Sathish Kasilingam, Ruoyu Yang, Shubhendu Kumar Singh, Mojtaba A. Farahani, Rahul Rai, Thorsten Wuest

Get full text

QR Food Ordering System with Data Analytics by Chee-Chun Wong, Lee-Ying Chong, Siew-Chin Chong, Check-Yee Law

“…Machine learning has become a huge trend nowadays, it is also included to in the proposed system to forecast more valuable data for the business.…”
Get full text

Machine Learning and data mining tools applied for databases of low number of records by Hubert Anysz

Subjects: “…machine learning…”
Get full text

Primer on machine learning applications in brain immunology by Niklas Binder, Ashkan Khavaran, Roman Sankowski

“…Traditional statistical techniques, adapted for single-cell omics, have been crucial in categorizing cell types and identifying gene signatures, overcoming challenges posed by increasingly complex datasets. We explore how machine learning, particularly deep learning methods like autoencoders and graph neural networks, is addressing these challenges by enhancing dimensionality reduction, data integration, and feature extraction. …”
Get full text

Analysis of goal, feedback and rewards on sustained attention via machine learning by Nethali Fernando, Nethali Fernando, Matthew Robison, Matthew Robison, Pedro D. Maia, Pedro D. Maia

“…Finally, we quantify changes in accuracy when coarser features (averaged throughout multiple trials) are used. Interestingly, the machine learning pipeline selects different features depending on their resolution, suggesting that predictive physiological features are also resolution-specific.DiscussionThese findings highlight the potential of machine learning to advance research on sustained attention and behavior, particularly in studies incorporating pupillometry or other physiological measurements, offering new avenues for understanding and analysis.…”
Get full text

Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

Subjects: Get full text

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

“…The agri-food sector is an endless source of expansion for nourishing a vast population, but there is a considerable need to develop high-standard procedures through intelligent and innovative technologies, such as artificial intelligence (AI) and big data. This paper addresses the research concerning AI and big data analytics in the food industry, including machine learning, artificial neural networks (ANNs), and various algorithms. …”
Get full text

A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

Get full text

Expediting Manufacturing Launch Using Integrated Data With AI/ML Analytic Solutions by Helen Haiying Yu, Scott Martin, Laurenz van der Meer, Edward Yang, Sherry Lee, Wanting Xiong, Vaishnavi Reddipalli, Richard Burch, Tomonori Honda, Jeffrey David

Get full text