Laboratory Informatics Weekly Update – Volume 18, Issue 50
December 29, 2020 Laboratory Informatics Weekly Update Volume 18, Issue 50 In This Issue Featured Books COVID-19 Testing, Reporting, and Information Management in the Laboratory Featured Content 12/30/2020 - Lab Informatics Insights 2020It’s typical for a service provider to stay up-to-date with industry happenings and to continually learn about their potential clients’ ever-changing needs. There are programs and measures in place to calculate and monitor these needs. At CSols, we developed a set of polls and quizzes to identify industry trends and collect feedback from those whom our lab informatics services can help. The respondents were contacts across various…Explainability for artificial intelligence in healthcare: A multidisciplinary perspective
Artificial intelligence (AI) is increasingly making its way into many aspects of health informatics, backed by a vision of improving healthcare outcomes and lowering healthcare costs. However, like many other such technologies, it comes with legal, ethical, and societal questions that deserve further exploration. Amann et al. do just that in this 2020 paper published in BMC Medical Informatics and Decision Making, examining the concept of "explainability," or why the AI came to the conclusion that it did in its task. The authors provide a brief amount of background before then examining AI-based clinical decision support systems (CDDSs) to provide various perspectives on the value of explainability in AI. They examine what explainability is from the perspective of technological perspective, then examine the legal, medical, and patient perspectives of explainability's importance. Finally, they examine the ethical implications of explainability using Beauchamp and Childress' Principles of Biomedical Ethics. The authors conclude "that omitting explainability in CDDSs poses a threat to core ethical values in medicine and may have detrimental consequences for individual and public health."Secure record linkage of large health data sets: Evaluation of a hybrid cloud model
This 2020 paper published in JMIR Medical Informatics examines both the usefulness of linked data (connecting data points across multiple data sets) for investigating health and social issues, and a cloud-based means for enabling linked data. Brown and Randall briefly review the state of cloud computing in general, and in particular with relation to data linking, noting a dearth of research on the practical use of secure, privacy-respecting cloud computing technologies for record linkage. Then the authors describe their own attempt to demonstrate a cloud-based model for record linkage that respects data privacy and integrity requirements, using three synthetically generated data sets of varying sizes and complexities as test data. They discuss their findings and then conclude that through the use of "privacy-preserving record linkage" methods over the cloud, data "privacy is maintained while taking advantage of the considerable scalability offered by cloud solutions," all while having "the ability to process increasingly larger data sets without impacting data release protocols and individual patient privacy" policies.
LIMS Validation – Get Yourself Armed with Knowledge This Festive Season
LIMS Validation can be a tricky subject to get your head round. This white paper provides a good background on what LIMS validation is, and the steps you need to go through to achieve it. Whatever LIMS software you are using the steps and the jargon are the same.
Grab a copy today and read it at your leisure:
[Download White Paper from Here]
Wishing you a happy festive season,
From Autoscribe Informatics and all in the LIMS world!
Risk assessment for scientific data
In this 2020 paper published in Data Science Journal, Mayernik et al. present their take on assessing risks to digital and physical data collections and archives, such that the appropriate resource allocation and priorities may be set to ensure those collections' and archives' future use. In particular, they present their data risk assessment matrix and its use in three different use cases. Noting that the trust placed in a data repository and how it's run is "separate and distinct" from trust placed in the data itself, the authors lay out the steps for assessing those repositories' risks, and then making that task easier through their risk assessment matrix. After presenting their use cases, they conclude that their matrix proves "a lightweight method for data collections to be reviewed, documented, and evaluated against a set of known data risk factors."How to Conduct Effective User Acceptance Testing
According to a report from Forbes, 25 percent of technology projects fail outright; 20 to 25 percent don’t show any return on investment; and as much as 50 percent need massive reworking by the time they’re finished.
Why is this the case? It is a complex question that likely comes with complex answers. Technical failures, scope creep, platform and performance issues, and the like all happen rampantly in enterprise IT organizations. [Read More]
How Labs Can Get Involved in COVID Screening Programs
Organizations, Businesses, Schools and Colleges everywhere need testing programs. Data-driven decision making has put laboratories squarely in the center of the COVID-19 pandemic response. Unfortunately, even CLIA-certified clinical diagnostic labs can’t contribute unless they have the resources to conduct COVID-19 molecular diagnostics testing. But now there may...
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Sunquest provides NGS Support from the Wet Bench to the Dry Lab
Molecular labs conducting next-generation sequencing (NGS) must analyze troves of data to interpret results. In addition to Sunquest Mitogen LIMS, Sunquest also offers Sunquest Mitogen Genetics. This powerful genomic analysis support software to helps labs more easily classify genetic variants and quickly produce clinically-actionable patient reports.
[Read More]
CSols University – SampleManager eLearning Courses
Promo code for December: GIFT40 to get 40% any or all three courses!
CSols University has a series of three online courses that can help. In just a few short hours you can go from beginner to report and workflow guru, for 40% off in the month of December with coupon code: GIFT40.
Gift yourself this month with in-depth SampleManager LIMS knowledge.
Laboratory Informatics Weekly Update – Volume 18, Issue 49
December 15, 2020 Laboratory Informatics Weekly Update Volume 18, Issue 49 In This Issue Featured Books Past, Present, and Future of Cannabis Laboratory Testing and Regulation in the United States Featured Content 12/15/2020 - How to Conduct Effective User Acceptance TestingAccording to a report from Forbes, 25 percent of technology projects fail outright; 20 to 25 percent don’t show any return on investment; and as much as 50 percent need massive reworking by the time they’re finished. Why is this the case? It is a complex question that likely comes with complex answers. Technical failures, scope creep, platform and performance…Cannabinoid, terpene, and heavy metal analysis of 29 over-the-counter commercial veterinary hemp supplements
While the push for the decriminalization of cannabis, its constituents, and the products made from them continues in the United States, issues of quality control testing and standardization persist. Consistent and accurate laboratory testing of these products is required to better ensure human health outcomes, to be sure. However, with the legalization of hemp, it's not just products intended for humans that are being created from hemp constituents such as cannabidiol (CBD); products marketed for our pets and other animals are appearing. And with them an inconsistent, sometimes dangerous lack of testing controls, or so finds Wakshlag et al. in this 2020 paper published in Veterinary Medicine: Research and Reports. The researchers review the regulatory atmosphere (or lack thereof) and then present the results of analytically testing 29 cannabis products marketed for dog use. They found wide-swinging variances in actual cannabinoid and contaminant content, straying often from labeled contents and contaminant standards. They conclude "the range and variability of [cannabis-derived] products in the veterinary market is alarming," and given the current state of regulation and standardization, "veterinary professionals should only consider manufacturers providing product safety data such as COAs, pharmacokinetic data, and clinical application data when clients solicit information regarding product selection."Data Visualization: Make the Most of Your Lab Informatics
You’ve probably seen the buzzwords data visualization, big data, and machine learning if you’ve been reading a lot in the last year or so. And who hasn’t been reading a lot during 2020—there’s not that much else to do! In this blog post, we’ll discuss some of the ways that data visualization tools can help you use accumulated data (even if it’s big data)... [Read More]
