Health systems evaluating AI must look beyond datasets and algorithms to understand the assumptions and priorities embedded within the applications themselves.

Abstract: Imbalanced data remains a challenge in classification research and significantly influences classifier performance. The strategy that is widely used to address this issue is the data-level ...

Low-rank data analysis has emerged as a powerful paradigm across applied mathematics, statistics, and data science. With the rapid growth of modern datasets in size, dimensionality, and complexity, ...

Russian Academy of Sciences, FSBIS Institute of Physiologically Active Compounds of the Russian Academy of Sciences, 1, Severny Proezd, Chernogolovka 142432, Russian Federation Russian Academy of ...

Welcome to the Data Structures and Algorithms Repository! My aim for this project is to serve as a comprehensive collection of problems and solutions implemented in Python, aimed at mastering ...

I kicked things off by tackling 10 problems centered around numbers. This helped refresh core mathematical concepts and basic programming logic.

One of the biggest barriers to using AI successfully is bias, which is one of the terms we defined last time, as follows: Bias, in a general context, refers to a predisposition or inclination towards ...

Our research group at the Instituto de Matemáticas of the Universidad Nacional Autónoma de México focuses in studying the principles underlying distributed computing, which covers a wide range of ...

Data structures and algorithms are crucial for efficient problem-solving in computer science, enabling effective data organization and manipulation for fast, reliable software. Learning them enhances ...