Empowering Stroke Research: Dr. Yasmin Aziz’s Journey with Nested Knowledge
In the ever-evolving field of stroke research, new questions about different therapies, trial outcomes, and even metrics of procedural success are constantly emerging, meaning that systematic reviews are needed on a consistent basis to extract all information needed to inform both patient care and future research. In these projects, because of the major decisions that may result from the findings and because of how busy stroke physicians are, the efficiency and accuracy are paramount.
Recently, we sat down for a conversation with Dr. Yasmin Aziz, a practicing neurologist and Assistant Professor in the Neurology and Rehabilitation Medicine Department at the University of Cincinnati (UC) Gardner Neuroscience Institute.
Nested Knowledge Will Be At ISPOR 2024
From helping you implement faster AI-assisted workflows which speed up your team by up to 75%, to helping you think through how to design your next project with the new JCA requirements in mind, Nested Knowledge has you covered. If there is a singular through line that ties these top trends together, it’s this: evidence synthesis is getting more complicated, not less.
Towards Patient-Centered Health Technology Assessment
While HTAs are designed to help payers–in some cases governments– allocate resources and control rising healthcare costs, patients are the ultimate stakeholders.
In the seventeen years since researchers first proposed “patient-based health technology assessments,” key institutions have made progress. PCORI, ICER, and other agencies invite patient comments on HTAs and listen to patients on their advisory panels.
Navigating the Sea of Knowledge: Assembling your First Review-Worthy Research Question
In just a few short paragraphs, we’ll guide you through the challenging process of assembling a review-worthy research question for your systematic literature review, likening it to the art of charting a course.
Not Systematic? That’s Ok!
Any medical researcher can tell you that systematic reviews are hard. It’s not just the difficulty of building out a research question/protocol/search strategy that is intimidating—there is also simply a large burden in screening and extraction to ensure the true comprehensiveness of the studies and data collected. However, not all questions are appropriate for systematic […]
10 Things to Keep in Mind When Setting Up Your First Nest
1. Understand What Nested Knowledge Is and What It Does Before you dive into all that Nested Knowledge (NK) has to offer, you should understand the two-fold nature of the software platform: AutoLit, and Synthesis. AutoLit is the workflow portion, enabling researchers to generate high-quality evidence, like systematic reviews and meta-analyses. Synthesis is the visualization, […]
Can ChatGPT Do Your Next Systematic Review?
I started where any literature review starts–by trying to construct a Search. I wanted to see if ChatGPT could generate a PubMed query that would yield similar initial search results to a human’s initial search string. I figured it would be easiest to simply try to replicate the initial search from a recently published review conducted by our research team in collaboration with two physicians from Stanford.
New Sources of Recurring Revenue for CROs: A case study from Nested Knowledge
Tech, meet experts. It’s a powerful force multiplier: using Nested Knowledge’s intelligent systematic review and evidence visualization software, experts at a top clinical research organization have built a living evidence library for their client, a leading pharmaceutical company in the diabetes space.
Extraction
June 3, 2022 This help article is about performing data extraction for meta-analyses in the NK Platform. If you just want basic instructions, feel free to check out this part of our wiki. Meta-Analytical Extraction is quite contentious at NK. It is one of those things you either love or hate with the fire of […]
Nested Knowledge’s Public-interest Reviews
October 31, 2021 Nested Knowledge supports a wide range of review and meta-analysis projects, mostly completed by external researchers using our novel software system, AutoLit. However, as part of our internal testing of software performance and in support of grant submissions demonstrating the viability of AutoLit, we have completed and made public the following research […]
