When you search UpToDate, you’ll now have access to VisualDx’s extensive image library, which includes thousands of images depicting diseases across various skin types and tones, covering a wide range of diagnoses and findings. For dermatologic conditions, where visual indicators are essential for accurate diagnosis, this integration is designed to improve diagnostic precision and streamline clinical decision-making.

Through our relationship with Elsevier and early participation in trial testing of Scopus AI, MSK was selected from a small group of research institutions to pilot early versions of GenAI features in ScienceDirect.

Currently in its Alpha phase, the ScienceDirect integrated GenAI tool may evolve throughout the trial period, which is expected to end late August 2024.

Features of the GenAI Tool:

• Enhanced Search: Provides a fast and efficient approach to information retrieval. Using natural language processing (NLP) capabilities and machine learning algorithms, this tool distills key insights from peer-reviewed content, accelerating the research process.
• Questions and Answers on the Article Page: This feature aims to help researchers find information faster and more efficiently by providing an at-a-glance view of key questions each article addresses. It includes direct links to relevant content in the full text for easy reference.
• Reading Assistant: Functions like a per-document Q&A tool.

Access to the GenAI Tool:

• A search in PubMed that retrieves any Elsevier journal article will take you to the ScienceDirect platform – https://pubmed.ncbi.nlm.nih.gov/29397066/ – where you can explore the new GenAI features.
• You can also access the GenAI features by searching the ScienceDirect platform directly.

These early versions, built on a selection of full-text journal and book content in the Life Sciences, can help researchers extract insights connected to their research question, either from one paper or from the entire corpus of content covered in this pilot. Each insight can be immediately traced back to its source paper or book chapter. More than 30 subject-matter experts have helped Elsevier refine the feature to ensure that the generated output is reliable, relevant, and accurate.

Elsevier will be collecting in-product feedback and surveys. Internally, we plan to work with users to get additional feedback. Your participation and feedback are valued.

If you have any questions regarding the pilot, please feel free to contact Mark Monakey at monakeym@mskcc.org.