HIGHLIGHTS What: The authors compare five machine_learning algorithms: kernel ridge regression (KRR), support vector regression (SVR), random forests (RF), neural_networks […]

HIGHLIGHTS What: The Article has exemplified that machine learning models are capable of predicating acceptancy by comparing patterns historic data

HIGHLIGHTS What: The aim of this in vitro study was to digitally assess the characteristics of and zirconia-reinforced pressable following

HIGHLIGHTS What: The authors explore how and digitalization are facilitating an expansion of domains for value extraction in a broad

HIGHLIGHTS What: Binary logistic regression models were calculated to investigate the dependence between age, body mass index (BMI), MRI-AGD-AC, MRI-AGD-AF,

HIGHLIGHTS What: The authors provide clinicians with a reference for managing different lymph node states, although there are still aspects

HIGHLIGHTS What: The authors focused analyses on comparing groups with respect to differential neural activation within regions of the extended

HIGHLIGHTS Who: Xingjun Mao from the Department of Urology, Baoying People`s Hospital, Xincheng Road, Baoying, Yangzhou, Jiangsu, China have published

HIGHLIGHTS Who: Mirko Pegoraro and collaborators from the Liverpool John Moores University, United Kingdom have published the paper: Chronobiology of

HIGHLIGHTS What: The authors finally show that it is possible to extend learning algorithms to general states obtained by Clifford+T