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Found 2 papers, 1 papers with code
Predicting Lung Disease Severity via Image-Based AQI Analysis using Deep Learning Techniques
The objective of this study is to devise an integrated approach for predicting air quality using image data and subsequently assessing lung disease severity based on Air Quality Index (AQI). The aim is to implement an integrated approach by refining existing techniques to improve accuracy in predicting AQI and lung disease severity.
NegBERT: A Transfer Learning Approach for Negation Detection and Scope Resolution
Our model, referred to as NegBERT, achieves a token level F1 score on scope resolution of 92. 36 on the Sherlock dataset, 95. 68 on the BioScope Abstracts subcorpus, 91. 24 on the BioScope Full Papers subcorpus, 90. 95 on the SFU Review Corpus, outperforming the previous state-of-the-art systems by a significant margin.
Ranked #2 on
Negation Scope Resolution
on SFU Review Corpus
(using extra training data)
