
An Introduction to AI Model Training for Life Sciences: Part 2
Taking a closer look at each of the four steps within the training phase of AI Model Training.
A Saama company that offers data analytics solutions and services for banking and capital markets, consumer goods, insurance, the public sector, and more.
Our perspective on AL/ML in the life sciences industry.
Taking a closer look at each of the four steps within the training phase of AI Model Training.
We’ll be covering the best practices for training AI models for life sciences, from data preparation to training methods, and more.
Here at Saama, we are continuously innovating, researching, and developing AI models for healthcare. Saama’s AI Research Lab is an in-house team of dedicated AI
When introducing AI to any part of clinical trials, its benefits and advantages often overshadow the very important considerations to make about its implementation. While
When we think of AI within clinical trials, we tend to focus on its benefits and use cases for data aggregation, management, and analysis. While
Within clinical data management (CDM), there are numerous data quality, structure, volume, and collection challenges that make the process overly complex and difficult to oversee.
Today we’ll be looking at AI’s applicability across clinical data management (CDM) in life sciences and how it improves CDM as a business process. Artificial Intelligence
Artificial Intelligence (AI) is the hot topic of pretty much every discussion surrounding innovation and digital transformation across industries, ranging from how it can help
We’ve explored what generative AI is and how it works in our previous blog post. Now, let’s examine some practical applications and use cases for