The increasing global demand for sustainable energy and carbon materials, alongside pressing environmental concerns, ...

A recent study explored rapid evaporative ionization mass spectrometry (REIMS) as a high-throughput, real-time alternative. By analyzing metabolomic fingerprints from pig neck fat, REIMS was combined ...

The integration of soft computing and machine learning into healthcare systems is increasing due to their effectiveness and precision (Javaid et al., 2022; Abdelaziz et al., 2018). In recent years, ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: Type 2 Diabetes Mellitus (T2DM) is a major global health concern, emphasizing the need for early detection to improve patient outcomes. This paper conducts a comparative study of four ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Machine Learning (ML) algorithms have revolutionized various domains by enabling data-driven decision-making and automation. The deployment of ML models on embedded edge devices, characterized by ...

Abstract: This paper explores the integration of machine learning applications in employee performance evaluation, addressing the limitations of traditional methods. The purpose is to highlight how ML ...

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...

Machine learning is rapidly emerging as a pivotal tool in plant tissue culture research, offering innovative approaches to optimise protocols, predict morphogenic responses, and streamline ...