Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

This program had absolutely nothing to do with race…but multi-variable equations.” That’s what Brett Goldstein, a former policeman for the Chicago Police Department (CPD) and current Urban Science ...

AI’s biggest constraint isn’t algorithms anymore. It’s data…specifically, high-quality, forward-looking data. It is the “Rare ...

Much of our reams of data sit in large databases of unstructured text. Finding insights among emails, text documents, and websites is extremely difficult unless we can search, characterize, and ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

As computing power has increased and data science has expanded into nearly every area of our lives, we have entered the age of the algorithm. While our personal and professional data is being compiled ...

Forbes contributors publish independent expert analyses and insights. I write about the broad intersection of data and society. The data-driven revolution is prefaced upon the idea that data and ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, proposed a quantum intelligent interconnected fault-tolerant consensus algorithm that deeply ...

There’s no doubt that data and algorithms play an important part in the modern workplace, but we shouldn’t forget the human component of our decisions. We have an overwhelming amount of number and ...