Strict ethical and professional standards should be applied to the development of algorithms with social impacts to recover public trust in the technology, according to a report by BCS, the Chartered ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

A new algorithm can identify the most predictive data points that a tipping point is near. Whether you're trying to predict a climate catastrophe or mental health crisis, mathematics tells us to look ...

"Medical Genomics" research group at ISTA "Data Science, Machine Learning, and Information Theory" research group at ISTA Al Depope, Jakub Bajzik, Marco Mondelli, and Matthew R. Robinson. 2026. Joint ...

Haoyu Cheng, Ph.D., assistant professor of biomedical informatics and data science at Yale School of Medicine, has developed a new algorithm capable of building complete human genomes using standard ...

Data science pays off when you stop pitching models and start solving the decisions that keep executives up at night.

Agency leaders need to begin to look at the tools and capabilities required to meet the White House’s Federal Data Strategy 2021 Action Plan. Among the strategy’s various action items, that includes a ...

Moving data science into production has quite a few similarities to deploying an application. But there are key differences you shouldn’t overlook. Agile programming is the most-used methodology that ...

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 ...