Agriculture is entering a profound period of transformation, driven by the accelerating integration of artificial intelligence (AI), machine learning, computer vision, autonomous sensing, and data-driven decision support [...]
Matheus Dalmolin, Karolayne S. Azevedo, Luísa C. de Souza, Caroline B. de Farias, Martina Lichtenfels, Marcelo A. C. Fernandes
This study investigates the use of machine learning (ML) models combined with explainable artificial intelligence (XAI) techniques to identify the most influential genes in the classification of five recurrent cancer types in women: breast cancer (BRCA), lung adenocarcinoma (LUAD…
Ifeanyi Anthony Okwor, Geeta Hitch, Saira Hakkim, Shabana Akbar, Dave Sookhoo, John Kainesie
Recent significant advances in the healthcare industry due to artificial intelligence (AI) and machine learning (ML) have been shown to revolutionize healthcare delivery by improving efficiency, accuracy, and patient outcomes. However, these technologies can face significant chal…
M. S. Shyam Sunder, Vinay Anand Tikkiwal, Arun Kumar, Bhishma Tyagi
Aerosols play a crucial role in the climate system due to direct and indirect effects, such as scattering and absorbing radiant energy. They also have adverse effects on visibility and human health. Humans are exposed to fine PM2.5, which has adverse health impacts related to car…
Antonio Jesús Banegas-Luna, Horacio Pérez-Sánchez
As machine learning (ML) transforms industries, the need for efficient model development tools using high-performance computing (HPC) and ensuring interpretability is crucial. This paper presents SIBILA, an AutoML approach designed for HPC environments, focusing on the interpreta…
Abdullah, Nida Hafeez, Carlos Guzmán Sánchez-Mejorada, Miguel Jesús Torres Ruiz, Rolando Quintero Téllez, Eponon Anvi Alex, et al.
This study presents a hybrid analytical framework that enhances project selection by achieving reasonable predictive accuracy through the integration of expert judgment and modern artificial intelligence (AI) techniques. Using an enterprise-level dataset of 10,000 completed softw…
Joaquim Carreras, Yara Yukie Kikuti, Masashi Miyaoka, Shinichiro Hiraiwa, Sakura Tomita, Haruka Ikoma, et al.
The prognosis of diffuse large B-cell lymphoma (DLBCL) is heterogeneous. Therefore, we aimed to highlight predictive biomarkers. First, artificial intelligence was applied into a discovery series of gene expression of 414 patients (GSE10846). A dimension reduction algorithm aimed…