However, algorithms are not a perfect answer. There are biases behind the data, and the construction of models is based on ...

Leveraging AI to help analyze and visualize data gathered from a variety of data sets enables data-driven insights and fast analysis without the high costs of talent and technology. In today's ...

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms—addressing a ...

Discover what black box models are, their applications in finance and investing, and examples of how they drive decision-making without revealing internal processes.

Quantum Algorithms Prerequisites Undergraduate algorithms (CSCI 3104), data structures (CSCI 2270), discrete mathematics (CSCI 2824) and two semesters of calculus, or equivalents. We will assume that ...

The HATRH is comprised of three, iteratively applied algorithms: a grouping algorithm to cluster assets into functional tiles, and two algorithms respectively related to group movement and individual ...

In the evolving landscape of blockchain technology, auditors face the challenge of reconciling its decentralized nature with stringent data privacy laws.

A new combination of inputs for the estimation of left ventricular filling pressure has shown to outperform those from guidelines published in 2016.

A cycle counting algorithm that will reduce a complex history into a series of discrete cycles is presented. The cycles determined by this technique are defined as closed stress-strain hysteresis ...