Nested Knowledge

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====== Artificial Intelligence in Nested Knowledge ======

Nested Knowledge offers a variety of AI-enhanced tools that make the systematic review process smoother and easier for users. Listed in order of when you would use each tool in the review process, here are **our four key AI features:**
===== RoboPICO =====

  * RoboPICO works to provide the most commonly reported terms of interest in [[:wiki:autolit:search:exploration|]] to help you build an effective search query. When you use the Search Exploration tool, RoboPICO automatically runs when you hit "Refresh Exploration." These terms can then be built into your search query.

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  * RoboPICO also auto-highlights identified Populations, Interventions, Comparators/Outcomes (PICOs) [[:wiki:autolit:screening:exclude#read_study_abstract|found in Abstracts]] during Screening to aid you to more efficiently make a decision on inclusion or exclusion of the record.

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===== Bibliomine =====

The [[:wiki:autolit:search:bibliomine|Nested Knowledge Bibliomine feature]] auto-extracts citations when you upload a pdf of any previous systematic review or landmark study and imports all cited references as records directly into your nest. This allows for fast updating of existing reviews and turns them into living reviews through quick implementation in the software. Alternatively, citation mining from an existing project pdf builds a solid foundation for a new project in your field of interest.

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===== Robot Screener =====

[[:wiki:autolit:screening:robot|]] replaces one human reviewer with an AI reviewer in nests with a Dual Screening mode. It does require training (50 adjudicated screening decisions and 10 advancements or inclusions) prior to being switched on, but continually trains itself thereafter. Then, a human adjudicator reviews the preliminary screenings and makes the final decision.

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===== Smart Tag Recommendations (Enterprise users only) =====

[[:wiki:autolit:tagging:tag_recommendations#smart_beta_tag_recommendations_for_enterprise_subscriptions_only|Smart Tag Recommendations]] uses OpenAI's GPT-4 to search each full text for the most relevant evidence to extract alongside a tag. This is unlike Standard Tag Recommendations (available to all) which performs a simple keyword search (Standard Tag Recommendations). This feature helps to better answer questions (in Form-based modes) and saves time reading through pdfs to retrieve the data of interest.

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