DistillerSR Description
Automate every stage in your systematic literature review to produce evidence-based research more quickly and accurately. DistillerSR automates literature collection, triage and assessment with AI and intelligent workflows. DistillerSR makes managing any project, no matter how large or small, easier. It can also be configured to produce transparent, audit-ready, and compliant literature reviews. DistillerSR integrates with data providers such as PubMed, automatic reviews updates, and AI-powered duplicative detection and removal. This makes it easier to search more efficiently. Automatically import new published references, keeping literature reviews current. You can detect duplicate citations and remove them, preventing bias and skew caused by studies that were included more than once. DistillerSR can reduce your screening burden by 60% DistillerSR makes it easier to get started on the later stages of your review faster and more accurately.
DistillerSR Alternatives
D&B Connect
Your first-party data can be used to unlock its full potential. D&B Connect is a self-service, customizable master data management solution that can scale. D&B Connect's family of products can help you eliminate data silos and bring all your data together. Our database contains hundreds of millions records that can be used to enrich, cleanse, and benchmark your data. This creates a single, interconnected source of truth that empowers teams to make better business decisions. With data you can trust, you can drive growth and lower risk. Your sales and marketing teams will be able to align territories with a complete view of account relationships if they have a solid data foundation. Reduce internal conflict and confusion caused by incomplete or poor data. Segmentation and targeting should be strengthened. Personalization and quality of marketing-sourced leads can be improved. Increase accuracy in reporting and ROI analysis.
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DataBuck
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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PubMed
PubMed® is an extensive repository featuring over 35 million citations related to biomedical literature, sourced from MEDLINE, life science journals, and various online books. Many of these citations provide links to full-text articles, which can be accessed through PubMed Central and the websites of publishers. This invaluable resource is designed to facilitate the search and retrieval of literature in the biomedical and life sciences, ultimately aiming to enhance health on both a global and individual level. Although the PubMed database does not host full-text journal articles directly, it often includes hyperlinks to such content when it is accessible from other platforms, such as the publisher's site or PubMed Central (PMC). The citations within PubMed primarily originate from fields related to biomedicine and health, as well as associated disciplines that encompass life sciences, behavioral sciences, chemical sciences, and bioengineering. A significant part of PubMed is made up of MEDLINE, which contains citations from journals that have been selectively included for its collection. Researchers and healthcare professionals frequently utilize this platform to stay informed on the latest developments and findings in medical research.
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Sciscoper
Sciscoper is an AI-driven research assistant designed to enhance and expedite the literature review process for professionals in STEM fields, including researchers, academics, and R&D teams. Given the challenge researchers face with managing extensive collections of scientific papers from various sources, extracting valuable insights can often become a cumbersome task.
To address this issue, Sciscoper leverages AI and natural language processing capabilities to automatically:
- Summarize scientific articles and research outcomes.
- Identify crucial insights, concepts, and interconnections within documents.
- Create literature reviews complete with citations in diverse referencing formats.
- Organize and categorize papers into a well-structured, searchable knowledge repository for convenient access.
As a result, users can minimize the time spent on tedious reading and note-taking, allowing them to concentrate more on analyzing findings, recognizing areas for further research, and contributing to the advancement of scientific knowledge. Ultimately, Sciscoper transforms the literature review process, making it more efficient and effective for its users.
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Pricing
Pricing Starts At:
$215 per user per month
Company Details
Company:
DistillerSR Inc.
Year Founded:
2008
Headquarters:
Canada
Website:
www.distillersr.com
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Product Details
Platforms
Web-Based
Types of Training
Training Docs
Live Training (Online)
Webinars
In Person
Customer Support
Business Hours
Live Rep (24/7)
Online Support
DistillerSR Features and Options
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