Abstract Machine learning techniques, especially deep learning, have achieved remarkable
breakthroughs over the past decade. At present, machine learning applications are …

Machine learning (ML) is used increasingly in real-world applications. In this paper, we
describe our ongoing endeavor to define characteristics and challenges unique to …

Background: The number of Machine Learning (ML) systems developed in the industry is
increasing rapidly. Since ML systems are different from traditional systems, these differences …

Data validation is an essential requirement to ensure the reliability and quality of Machine
Learning-based Software Systems. However, an exhaustive validation of all data fed to …

Abstract The Digital Age, the “Society 5.0” or the “4th Industrial Revolution” has created a
challenging and evolving environment in which more up‐to‐date, secure, safer, cost …

Recent progress in artificial intelligence (AI) using deep learning techniques has triggered
its wide-scale use across a broad range of applications. These systems can already perform …

Providing a multi-modal user interface adds value to any application. Allowing users to
speak or chat with the system is one such area where software practitioners are putting a lot …

In the last couple of years we have witnessed an enormous increase of machine learning
(ML) applications. More and more program functions are no longer written in code, but learnt …

There is an increasing demand of digitalization technologies in almost all aspects in modern
life. A swelling part of these technologies and solutions are based on Machine Learning …

Background: We propose a novel framework for health Informatics: framework and
methodology of Software Engineering for machine learning in Health Informatics (SEMLHI) …