|
|
|
|
|
Daniel Einarson, Fredrik Frisk, Kamilla Klonowska and Charlotte Sennersten
Machine learning (ML) is increasingly used in diverse fields, including animal behavior research. However, its application to ambiguous data requires careful consideration to avoid uncritical interpretations. This paper extends prior research on ringed m...
ver más
|
|
|
|
|
|
|
|
|
Alejandro Valencia-Arias, Juan David González-Ruiz, Lilian Verde Flores, Luis Vega-Mori, Paula Rodríguez-Correa and Gustavo Sánchez Santos
Machine learning and blockchain technology are fast-developing fields with implications for multiple sectors. Both have attracted a lot of interest and show promise in security, IoT, 5G/6G networks, artificial intelligence, and more. However, challenges ...
ver más
|
|
|
|
|
|
|
|
|
Marco Leo, Pierluigi Carcagnì, Luca Signore, Francesco Corcione, Giulio Benincasa, Mikko O. Laukkanen and Cosimo Distante
Colorectal cancer is one of the most lethal cancers because of late diagnosis and challenges in the selection of therapy options. The histopathological diagnosis of colon adenocarcinoma is hindered by poor reproducibility and a lack of standard examinati...
ver más
|
|
|
|
|
|
|
|
|
Károly Héberger
Background: The development and application of machine learning (ML) methods have become so fast that almost nobody can follow their developments in every detail. It is no wonder that numerous errors and inconsistencies in their usage have also spread wi...
ver más
|
|
|
|
|
|
|
|
|
Hamed Taherdoost and Mitra Madanchian
In recent years, artificial intelligence (AI) has seen remarkable advancements, stretching the limits of what is possible and opening up new frontiers. This comparative review investigates the evolving landscape of AI advancements, providing a thorough e...
ver más
|
|
|
|