Our perspective on AL/ML in the life sciences industry.
Healthcare data generates an astonishing 30% of the world’s total data, yet 80% of it remains unstructured- trapped in clinical notes, research papers, and disparate
Artificial Intelligence (AI) and Machine Learning (ML) have become key players in reshaping how we develop drugs, but with this potential comes the critical need
We’ll be covering the best practices for training AI models for life sciences, from data preparation to training methods, and more.
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
No matter what your core focus is as a life sciences organization, manual data review is laborious and time-consuming, and vulnerable to human errors. A
Patients’ safety is the top priority in any clinical trial. The data safety and monitoring services (DSMC) are there to ensure that the clinical studies
One of the major challenges of managing clinical trials is collecting and applying relevant and important performance metrics. These Key Performance Indicators (KPIs) are used
