Abstract Decision Trees (DTs) are predictive models in supervised learning, known not only
for their unquestionable utility in a wide range of applications but also for their interpretability …

The frequent outbreak of global infectious diseases has prompted the development of rapid
and effective diagnostic tools for the early screening of potential patients in point-of-care …

Background Little is known about factors associated with hospitalization and critical illness
in Covid-19 positive patients. Methods We conducted a cross-sectional analysis of all …

In nature, snowflake ice crystals arrange themselves into diverse symmetrical six-sided
structures. We show an analogy of this when zinc (Zn) dissolves and crystallizes in liquid …

Over the last decade, IoT platforms have been developed into a global giant that grabs every
aspect of our daily lives by advancing human life with its unaccountable smart services …

Background Food flavor is a key factor affecting sensory quality. Predicting and regulating
flavor can result in exceptional flavor characteristics and improve consumer preferences and …

Understanding and quantifying the effects of risk factors on crash frequency is of great
importance for developing cost-effective safety countermeasures. In this paper, the effects of …

Nowadays, in the international scientific community of machine learning, there exists an
enormous discussion about the use of black-box models or explainable models; especially …

Inspired by natural biological systems, soft robots have recently been developed, showing
tremendous potential in real‐world applications because of their intrinsic softness and …

The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest developing fields in …