Data Analysis and Informatics
For many decades mankind has looked to automate tedious and error-prone steps of biomedical research in an attempt to improve reproducibility and throughput. While automation has had a large beneficial effect on overall throughput of biomedical research, reproducibility is still facing a crisis. In this talk, we will discuss automation trends in data generation, collection and analysis in the biomedical sciences and show how carefully designed digital tools can improve reproducibility while integrating humans in the loop. We will review both currently available and future-looking technology that are key to the laboratory of the future (e.g.: augmented reality, machine/statistical learning, voice assistants, etc). We will also discuss the need for a new framework that focuses on using machines and software to augment human scientists in the laboratory.