Data Scientist Yi Nian has advanced Alzheimer’s research at the University of Texas Health Science Center, highlighting machine learning’s role in accurate ADRD risk prediction. His work addresses the ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

Opinions expressed by Digital Journal contributors are their own. “In a world driven by data, my mission is to create innovative AI solutions that not only solve complex problems but also push the ...

Intelligent organizations prioritize investments in machine learning and real-time data to improve decision making, accelerate revenue generation efforts, reduce operational expenses and protect ...

Data science and machine learning technologies have long been important for data analytics tasks and predictive analytical software. But with the wave of artificial intelligence and generative AI ...

Antigen presentation by major histocompatibility complex (MHC) proteins is the caller ID of the immune system. On the cell surface, MHCs display peptides derived from cellular components or foreign ...

Both fields are in high demand, pay well, and lead to exciting, future-proof careers. If you're deciding between becoming a data scientist or an AI engineer, the choice often comes down to what ...

Machine learning (ML) is a subset of artificial intelligence (AI) that involves using algorithms and statistical models to enable computer systems to learn from data and improve performance on a ...

One problem with this new approach is that scRNA-seq and spatial transcriptomics are expensive and have limited clinical applications as they are not routinely assayed as part of cancer diagnosis.