What is a LIMS and ELN, and how do you know which to use? Laboratory automation expert Joe Liscouski reviews the two informatics applications and delves into discussion on which to use when. [Read More]
Today, most laboratories produce extensive amounts of data that come from different sources. These sources are typically not integrated which causes data silos and other challenges, driving the need for a successful LIMS selection and implementation. [Read More]
As anyone who has tried to fill Life Science positions lately can tell you, skilled individuals in a handful of industry sectors have become extremely difficult to find and hire. Growth in the Life Sciences industry is underscored by what’s happening in the real estate market. [Read More]
While the LIMS implementation is a big undertaking, there are ways to prepare ahead of time to keep the process manageable and streamlined. Check out what we recommend you know before beginning the implementation process.
In a 2018 article in The Journal of Molecular Diagnostics (JMD), the authors identified critical gaps in functionality in laboratory information systems (LIS) for molecular labs. To continue the conversation, we collaborated with the Cleveland Clinic’s Molecular Pathology Section lab team on a response. [Read More]
Artificial intelligence (AI) has been discussed in many healthcare contexts over the years, and this includes within the medical imaging field. But how aware are imaging specialists of AI and machine learning (ML) methods in imaging informatics, and what knowledge gaps must be filled to address concerns about misuse of patient safety with AI and ML in medical imaging? This survey-based research by Eiroa et al. examines the responses to numerous questions related to AI and ML by Spanish radiologists and suggests there are several information gaps that must be addressed. After a brief introduction and discussion concerning the survey methods, the authors present their results in numerous tables and images, followed by a discussion of that data in the scope of current and new radiologists entering the field. They conclude that "there is a general lack of knowledge about AI, ML, and related topics among Spanish radiologists, including both members in training and attending physicians," though there was an eagerness to learn and little fear of such automated methods taking away radiology jobs. They add that "there is no doubt that a common consensus is needed to change the current training curriculum to prepare new radiologists for a future world in which AI will undoubtedly shape the profession."