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NLP-Powered Data Extraction for SLRs and Meta-Analyses

Towards AI

Natural Language Processing Getting desirable data out of published reports and clinical trials and into systematic literature reviews (SLRs) — a process known as data extraction — is just one of a series of incredibly time-consuming, repetitive, and potentially error-prone steps involved in creating SLRs and meta-analyses.

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Systematic Reviews in NLP

Ehud Reiter

Over the past year I have on several occasions encouraged NLP researchers to do systematic reviews of the research literature. I In AI and NLP, most literature surveys are like “previous work” sections in papers. The Data extracted : what information we extract from the paper. For

NLP 141
professionals

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Introduction to Large Language Models (LLMs): An Overview of BERT, GPT, and Other Popular Models

John Snow Labs

Are you curious about the groundbreaking advancements in Natural Language Processing (NLP)? Prepare to be amazed as we delve into the world of Large Language Models (LLMs) – the driving force behind NLP’s remarkable progress. Ever wondered how machines can understand and generate human-like text?

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ML and NLP Research Highlights of 2020

Sebastian Ruder

The selection of areas and methods is heavily influenced by my own interests; the selected topics are biased towards representation and transfer learning and towards natural language processing (NLP). 2018 ; Howard et al.,  2020 saw the development of ever larger language and dialogue models such as Meena ( Adiwardana et al.,

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Computer Vision and Deep Learning for Healthcare

PyImageSearch

Health startups and tech companies aiming to integrate AI technologies account for a large proportion of AI-specific investments, accounting for up to $2 billion in 2018 ( Figure 1 ). AI can also perform data extraction, search systematic reviews, and assess health technology.

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Amazon Textract’s new Layout feature introduces efficiencies in general purpose and generative AI document processing tasks

AWS Machine Learning Blog

For these tasks, we use the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metric to evaluate the performance of an LLM on question-answering tasks with respect to a set of ground truth data. Extractive tasks refer to activities where the model identifies and extracts specific portions of the input text to construct a response.

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Large Language Models in Pathology Diagnosis

John Snow Labs

As we navigate the complexities associated with integrating AI into healthcare practices our primary focus remains on using this technology to maximize its advantages while protecting rights and ensuring data privacy. Such capabilities allow for earlier intervention and personalized treatment strategies, markedly improving patient outcomes.