Our perspective on AL/ML in the life sciences industry.
Clinical trials are experiencing a major transformation. While the core goal remains bringing safe, effective treatments to patients, how we reach that goal is changing
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
The European Union recently released its comprehensive AI Act, marking a watershed moment as the world’s first-ever legal regulatory framework specifically designed to govern artificial
Clinical trials have long been a critical, but complex and costly part of drug development. However, with the rise of Artificial Intelligence (AI) & Machine
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
Generative AI (GenAI) holds enormous potential across a wide range of use cases in the clinical development space, but its tendency to hallucinate must be
In an industry as dynamic and complex as life sciences, the need for technological innovation is constant. With the increasing demand for faster clinical trials
Taking a closer look at hallucinations, why they occur, and how to limit them, especially if you’re in the process of training an AI model.
Taking a closer look at the intricacies and considerations necessary for successful ML model selection and training.
