Genetic risk models and variant classification tools are refining breast cancer risk assessment by identifying high-risk ...

Objectives Delays in cancer diagnosis for patients with non-specific symptoms (NSSs) lead to poorer outcomes. Rapid ...

The online information landscape, driven in large part by social media, rewards engagement and is curated by classification ...

Binary classification is a type of image classification where you essentially train a model on two different labelled objects ...

The review found that legal use cases are routinely broken down into tasks that do not reflect the complexity of legal ...

ABSTRACT: This paper deals with three traditional measures of concentration: (Corrado) Gini coefficient, adjusted Gini coefficient, and AUC. These metrics are popular methods in assessing the ...

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

The Babylonians used separate combinations of two symbols to represent every single number from 1 to 59. That sounds pretty confusing, doesn’t it? Our decimal system seems simple by comparison, with ...

School of Dentistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada Introduction: Accurate assessment of midpalatal suture (MPS) maturation is critical in orthodontics, ...

The Carnegie Foundation for the Advancement of Teaching and the American Council on Education debut a new classification system focused on student success. As widespread public skepticism about the ...

Eastern Cooperative Oncology Group performance status (ECOG PS) is a key confounder in comparative effectiveness research, predicting treatment and survival, but is often incomplete in electronic ...