Food informatics: Review of the current state-of-the-art, revised definition, and classification into the research landscape

Posted on April 5, 2022 By LabLynx Journal articles

Informatics, the study of information processing and management, has moved into many industries over the past few decades, and the food manufacturing and testing field is no different. Food informatics has evolved as a sub-branch of informatics that assesses how food-related activities can be improved for not only manufacturers but also consumers, using information technologies. This 2021 paper by Krupitzer and Stein examines the state of food informatics and proposes an updated definition that encompasses the state-of-the-art in food technologies and how they are used in the manufacturing and research landscape. After discussing numerous concepts important to food informatics, the authors propose their own definition and discuss how it applies to the practical use of tools like autonomous robotics, artificial intelligence (AI), machine learning (ML), internet of things (IoT), predictive maintenance, and more. They conclude that while "various research streams focus on different aspects of the production process ... they miss the methods and approaches that can be applied across several steps along the food production process." They add that the mindful addition of technologies like AI and IoT has high potential "to optimize the various aspects and processes concerning food production, consumption, and security."

Creating learning health systems and the emerging role of biomedical informatics

Posted on March 29, 2022 By LabLynx Journal articles

In this 2022 paper published in the journal Learning Health Systems, Kohn et al. of Wake Forest School of Medicine's Center for Biomedical Informatics describe the evolution of an academic biomedical informatics program in the scope of a "learning health system" (LHS) and improving decision making in the clinical field. The authors first provide background information on topics such as artificial intelligence (AI) and machine learning (ML) and how they they are trained upon and accepted within the clinical community. They then describe the concept of the LHS and what is required to understand and utilize it well, followed by full details of their biomedical informatics program and its incorporation of LHS at Wake Forest. The authors conclude that programs such as its Clinical Scholars in Informatics (CSI) program "can be broadly applied to most internal medicine programs across the United States" and that such programs clearly provide "bidirectional net benefits for the resident physicians and for the health system as a whole." They add that enabling clinical students in "understanding the role of AI and predictive analytics, and how to apply them, will become progressively more important" as the era of big data continues to grow.

Planning for Disruptions in Laboratory Operations

Posted on March 22, 2022 By LabLynx Journal articles

Most know that the COVID-19 pandemic turned a solid chunk of the workforce—and their work itself—on its heels. More than two years later, this change has both positively and negatively affected many a workplace, including the laboratory. In this March 2022 work by laboratory veteran Joe Liscouski, the impact of disruptions like COVID-19, flooding, and power failure to laboratories is discussed, particularly within the scope of implementing automation to better limit those disruptions. However, as Liscouski notes, it's not as simple as "let's implement laboratory automation"; many nuances to its implementation and use exist within the context of laboratory work. The author first discusses the nature of work itself, followed by a brief look at laboratory work. He then examines eight talking points about using automation to prevent disruptions in on-site laboratory activities, as well as a few critical points about the laboratory work that can be done remotely. He finishes by discussing other external disruptions to laboratory work, including meteorological issues, natural disasters, power disruptions, and supply chain issues. Liscouski concludes that while laboratory automation is here to stay by improving workflows and limiting disruptions, we must implement it with care and deliberate planning in order to make the most of it.