Newly published research provides a valuable method that may be useful for designing unique, functional proteins for therapeutic and diagnostic applications. Author: Jayvee Abella The Baker Lab at the University of Washington recently published a very interesting approach for finding novel proteins using an iterative, inverted technique (sometimes called hallucination)…

Harnessing the power of AI/ML has the potential to transform health tech and medical device companies by providing better outcomes, better patient and provider satisfaction and engagement, and better insight into product performance and real world evidence. Authored by: Dan Watkins, Michael Bell, and Angela Holmes Increasingly health tech and…

Predicting emotion from video is increasingly a part of applications spanning healthcare and the life sciences. Major cloud service providers offer off-the-shelf emotion prediction APIs, but accuracy and interpretability often fail to meet the needs of our clients. Read how our team developed a new approach to predict emotions from…

Learn about the approach and impact of the model we built to predict skin tone from face images and videos using a unique combination of computer vision and machine learning to help organizations monitor for racial biases in large datasets. Written by: Michael Bell, Daniel Chen, Jenna Cicardo, Maya Waterland …

Here is what we see as the most valuable high impact trends in AI/ML for life sciences and healthcare Authors: Angela Holmes & Dan Watkins As a Full Stack AI/ML consultancy, focused on helping life science and healthcare clients develop new AI-based products and tools, we spend a lot of time thinking about new AI/ML applications. …

Authors: Angela Holmes & John Aven Five challenges and solutions critical to the success of Data Science in Healthcare and Life Sciences Data is supremely important in life sciences and healthcare. Multi-omic analyses yield clues to biomarkers of disease and possible drug targets. In the ag biotech world, genome wide association studies (GWAS) provide paths to gene editing targets for more nutritious and sustainable food crops…

Why companies need to think ahead about infrastructure for data science Authors: Michael Bell & Dan Watkins After months of hard, careful work exploring data and training models, your data team is finally ready to push their best model to production; you may think the ML project is done but the fact is that deploying an ML model is just the…

Author: Julie Mocko Success in pursuit of discovery and development begins with a thorough understanding of what has been discovered, what is actively being explored, what has worked, what has failed, and what questions remain unanswered. The solution: Literature review. The problem: An unwieldy and ever-growing mountain of literature rife…