Objective: Identifying fraud in healthcare programs is crucial, as an estimated 3%–10% of
the total healthcare expenditures are lost to fraudulent activities. This study presents a …

The healthcare datasets are used in machine intelligence-based systems to predict the
ailments. The robotic surgeries and robotic procedures also use the healthcare datasets for …

Classification is one of the main areas of machine learning, where the target variable is
usually categorical with at least two levels. This study focuses on deducing an optimal cut …

Wireless sensor networks have revolutionized the way healthcare works replacing the
traditional methods with sensor-enabled IoT devices that help in monitoring the data. The …

Fraudulent or wasteful medical insurance claims made by health care providers are costly
for insurers. Typically, OECD healthcare organisations lose 3-8% of total expenditure due to …

The healthcare industry rapidly adopts digital technologies to improve patient care and
outcomes. However, this digital transformation has also made healthcare systems more …

Determining appropriate premiums for policyholders is a challenge faced by the healthcare
insurance industry. Policyholders' judgments about their healthcare are negatively impacted …

This work introduces a method for Quality Assurance of Artificial Intelligence (AI) Systems,
which identifies and characterizes “corner cases”. Here, corner cases are intuitively defined …

Mechanical devices in industriy are equipped with numerous sensors to capture the health
state of the machines. The reliability of the machine's health system depends on the quality …

Zusammenfassung Der Einsatz von Robotersystemen hat in den letzten Jahren in
verschiedenen Anwendungsbereichen zunehmend an Bedeutung gewonnen. Dies erfordert …