YData for Healthcare & Pharma

Improved and synthetic data for AI

AI has been widely used in clinical situations to diagnose diseases and aid medical professionals in deciding the course of treatment. Data collection is however one of the biggest challenges faced by the Healthcare organisations - it is critical that medical data is shared across organisations, enabling them to provide patients with the best possible healthcare solutions.

Read more

Use cases for Healthcare & Pharma

Access to patients’ data

Data is the prime matter and needs to be accessible

Organisations cannot share patients’ data directly due to concerns around privacy. A lot more problems could be solved if patients’ data could be shared across organisations without impacting their privacy. YData enables easy sharing of data both within internal teams and external organisations.

Data augmentation

Overcome lack of data and data silos

In critical domains such as this data often exists in silos, which insufficient to train a good model. Data augmentation is a proven method to work around this problem. YData accomplishes this without any unintended side-effects by synthesizing data without changing its inherent nature.

Isometric square pattern

Handling bias

Balance your datasets to save more lives

ML models are being used in the clinical domain often for diagnosis purposes. The dataset can turn out heavily imbalanced if the subject selection is not done properly. Using our Synthesizers, you can balance the dataset and make sure that your model is not trained on the wrong data.

Getting started is easy

What's your main purpose in contacting us?*

Thank you! We'll get in touch with you soon.

Our most recent articles

From model-centric to data-centric

A new paradigm for AI development — focused on data quality

Read more
High-quality data meets enterprise MLOps

According to the 2021 enterprise trends in machine learning report by Algorithmia

Read more
The rise of DataPrepOps

Modern data development tools and how data quality impacts ML results

Read more