Currently, deep learning is the most important technique for solving many complex machine vision problems. State-of-the-art deep learning models typically contain a very large number of parameters ...

In a recent study published in the journal Nature Medicine, researchers used diffusion models for data augmentation to increase the robustness and fairness of medical machine learning (ML) models in ...

Real-world data (RWD) is transforming clinical research, augmenting existing randomized controlled trial (RCT) data to de-risk studies and improve generalizability. With regulators setting clearer ...

Strict data privacy regulations have compelled companies to transition to using synthetic data, the ideal substitute for real data, containing similar insights and properties yet is more privacy-safe ...

How do you fix the very real problem of missing or flawed data in healthcare? Just make new data, says a leading academic. But is it as simple as that? In my previous reports on the challenges of ...

Synthetic data generation (SDG) was proposed in the early nineties as a form of imputation. 1 Since then, multiple statistical and machine learning (ML) methods have been developed to generate ...

The data analytics and AI software giant is buying the intellectual property assets of synthetic data pioneer Hazy, SAS said Tuesday. Data analytics and AI software developer SAS is boosting its ...

Advancements in Natural Language Processing (NLP) models and generative artificial intelligence (GAI) models have fundamentally changed the way that we think of human interaction—think AI chatbots and ...

As India enters a decisive year for AI adoption, enterprises that embed privacy, data discipline and skills early will scale ...

Forbes contributors publish independent expert analyses and insights. Creating the future of AI, Integrity over Intelligence. This claim is made in the context of explaining that the limitation for AI ...