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.
Learn more
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.
Learn more
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.
Learn more
MEDLINE
MEDLINE serves as the flagship bibliographic database of the National Library of Medicine (NLM), boasting over 29 million references to journal articles primarily focused on life sciences and biomedicine. One of the unique aspects of MEDLINE is its use of NLM Medical Subject Headings (MeSH) for indexing records, which enhances searchability and organization. It plays a crucial role as the foundational component of PubMed, a comprehensive literature database managed by the NLM's National Center for Biotechnology Information (NCBI). MEDLINE is essentially the digital evolution of the MEDical Literature Analysis and Retrieval System (MEDLARS), which was established in 1964. The selection of journals for inclusion in MEDLINE largely relies on the recommendations made by the Literature Selection Technical Review Committee (LSTRC), which comprises external experts appointed by the NIH. The database encompasses literature published from 1966 to the present day, alongside select works from earlier years, thereby providing a rich historical context for researchers. Overall, MEDLINE stands as a critical resource for professionals seeking reliable and organized biomedical literature.
Learn more
Pricing
Pricing Starts At:
$215 per user per month
Company Details
Company:
DistillerSR Inc.
Year Founded:
2008
Headquarters:
Canada
Website:
www.distillersr.com
Media
Recommended Products
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas provides built-in vector search and a flexible document model so developers can build, scale, and run gen AI apps without stitching together multiple databases. From LLM integration to semantic search, Atlas simplifies your AI architecture—and it’s free to get started.
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
DistillerSR User Reviews
Write a Review- Previous
- Next
