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Extracting Semantic Aspects for Structured Representation of Clinical Trial Eligibility Criteria
Eligibility criteria in the clinical trials specify the characteristics that a patient must or must not possess in order to be treated according to a standard clinical care guideline.
ATL at FinCausal 2022: Transformer Based Architecture for Automatic Causal Sentence Detection and Cause-Effect Extraction
We describe our submission to the FinCausal 2022 shared task based on this method.
Mapping Patient Trajectories: Understanding and Visualizing Sepsis Prognostic Pathways from Patients Clinical Narratives
In recent years, healthcare professionals are increasingly emphasizing on personalized and evidence-based patient care through the exploration of prognostic pathways.
Learning Domain Terms - Empirical Methods to Enhance Enterprise Text Analytics Performance
Performance of standard text analytics algorithms are known to be substantially degraded on consumer generated data, which are often very noisy.
CLAIMED: A CLAssification-Incorporated Minimum Energy Design to explore a multivariate response surface with feasibility constraints
Motivated by the problem of optimization of force-field systems in physics using large-scale computer simulations, we consider exploration of a deterministic complex multivariate response surface.
Leveraging Web Based Evidence Gathering for Drug Information Identification from Tweets
Our evaluation results shows that the proposed model achieved good results, with Precision, Recall and F-scores of 78. 5{\%}, 88{\%} and 82. 9{\%} respectively for Task1 and 33. 2{\%}, 54. 7{\%} and 41. 3{\%} for Task3.
Automatic Curation and Visualization of Crime Related Information from Incrementally Crawled Multi-source News Reports
We have done experiments with a collection of 5000 crime-reporting News articles span over time, and multiple sources.
Automatic Extraction of Causal Relations from Text using Linguistically Informed Deep Neural Networks
In this paper we have proposed a linguistically informed recursive neural network architecture for automatic extraction of cause-effect relations from text.
Augmenting Textual Qualitative Features in Deep Convolution Recurrent Neural Network for Automatic Essay Scoring
In this paper we present a qualitatively enhanced deep convolution recurrent neural network for computing the quality of a text in an automatic essay scoring task.
A Framework for Mining Enterprise Risk and Risk Factors from News Documents
Any real world events or trends that can affect the company{'}s growth trajectory can be considered as risk.
Design and Development of an Online Computational Framework to Facilitate Language Comprehension Research on Indian Languages
In this paper we have developed an open-source online computational framework that can be used by different research groups to conduct reading researches on Indian language texts.
