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 ...

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 ...

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 ...

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 ...

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 ...

Rare disease is a major – and growing – area of clinical research and drug development. Of the FDA’s 46 novel drug approvals ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...