Serena Jeblee


2019

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Extracting relevant information from physician-patient dialogues for automated clinical note taking
Serena Jeblee | Faiza Khan Khattak | Noah Crampton | Muhammad Mamdani | Frank Rudzicz
Proceedings of the Tenth International Workshop on Health Text Mining and Information Analysis (LOUHI 2019)

We present a system for automatically extracting pertinent medical information from dialogues between clinicians and patients. The system parses each dialogue and extracts entities such as medications and symptoms, using context to predict which entities are relevant. We also classify the primary diagnosis for each conversation. In addition, we extract topic information and identify relevant utterances. This serves as a baseline for a system that extracts information from dialogues and automatically generates a patient note, which can be reviewed and edited by the clinician.

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Can Character Embeddings Improve Cause-of-Death Classification for Verbal Autopsy Narratives?
Zhaodong Yan | Serena Jeblee | Graeme Hirst
Proceedings of the 18th BioNLP Workshop and Shared Task

We present two models for combining word and character embeddings for cause-of-death classification of verbal autopsy reports using the text of the narratives. We find that for smaller datasets (500 to 1000 records), adding character information to the model improves classification, making character-based CNNs a promising method for automated verbal autopsy coding.

2018

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Multi-task learning for interpretable cause of death classification using key phrase prediction
Serena Jeblee | Mireille Gomes | Graeme Hirst
Proceedings of the BioNLP 2018 workshop

We introduce a multi-task learning model for cause-of-death classification of verbal autopsy narratives that jointly learns to output interpretable key phrases. Adding these key phrases outperforms the baseline model and topic modeling features.

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Listwise temporal ordering of events in clinical notes
Serena Jeblee | Graeme Hirst
Proceedings of the Ninth International Workshop on Health Text Mining and Information Analysis

We present metrics for listwise temporal ordering of events in clinical notes, as well as a baseline listwise temporal ranking model that generates a timeline of events that can be used in downstream medical natural language processing tasks.

2014

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CMUQ@QALB-2014: An SMT-based System for Automatic Arabic Error Correction
Serena Jeblee | Houda Bouamor | Wajdi Zaghouani | Kemal Oflazer
Proceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing (ANLP)

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Domain and Dialect Adaptation for Machine Translation into Egyptian Arabic
Serena Jeblee | Weston Feely | Houda Bouamor | Alon Lavie | Nizar Habash | Kemal Oflazer
Proceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing (ANLP)