Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance ...

Time-to-event is a powerful statistical approach increasingly used in sports science and medicine to examine time-to-event outcomes such as time to sports injury occurrence, career duration and ...

With nearly two decades of retail management and project management experience, Brett Day can simplify complex traditional and Agile project management philosophies and methodologies and can explain ...

ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...

Wrapping up a multi-week series on Crafting Data Personas. What are they, why are they important, and how to get started. Continuing from last week, we’re diving right into examples of personas. I ...

Christine E. Lynn College of Nursing, Florida Atlantic University, Boca Raton, FL, USA. Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional ...

Most of what we understand about eviction trends in a given city or county comes from local court records. Often the best way to access these records is through a data request. This resource includes ...

In today’s data-driven world, data entry skills are more valuable than ever. Most data entry roles require a high school diploma or GED, making them accessible to a wide range of job seekers. Whether ...

I read your paper, and you referred to the possibility of integrating different datasets, such as histopathology images, clinical notes, and sensor data. In the tutorials, you used floating data. I ...

Noticed a problem while taking a look at the examples in this repository. It's barely noticeable, but there is a mistake in the “Ordinal Data” example. In this example the line color gradient was ...